last patient last visit clinical trial

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Dow futures, nasdaq futures, russell 2000 futures, bitcoin usd, cmc crypto 200, last patient last visit completed in innovation pharmaceuticals’ phase 2 clinical trial of brilacidin for covid-19; trial database undergoing review in preparation for database lock.

WAKEFIELD, Mass., Aug. 12, 2021 (GLOBE NEWSWIRE) -- Innovation Pharmaceuticals (OTCQB:IPIX) (“the Company”), a clinical stage biopharmaceutical company, today provided additional information regarding the status of its randomized, double-blind, placebo-controlled Phase 2 clinical trial of Brilacidin for the treatment of moderate-to-severe COVID-19 in hospitalized patients (see NCT04784897 ). The Company is developing Brilacidin for treatment of COVID-19 under U.S. FDA Fast Track designation.

Full enrollment in the 120-patient clinical trial was completed in early June 2021. The last patient follow-up visit occurred on July 30, 2021. The subject database remains blinded with the current emphasis on confirmation of all data entered at study sites, as well as completion of source data verification and the necessary checks and reviews by the data management vendor in preparation of database lock.

Following database lock and transfer to the biostatistics vendor, analysis of the unblinded data from the clinical trial will begin to assess Brilacidin’s performance, against placebo, across primary, secondary, and other endpoints. Topline results are anticipated to be available one week after database lock, with full analysis to follow.

“Our team is as excited as anyone to learn the results of our Brilacidin COVID-19 clinical trial. Everything is advancing per industry norms and standards,” said Leo Ehrlich, Chief Executive Officer at Innovation Pharmaceuticals. “We look forward to sharing Brilacidin topline data in treating COVID-19 as soon as we have it in hand.”

About Brilacidin and COVID-19

Brilacidin is the only non-peptidic defensin-mimetic drug candidate currently in a clinical trial as a treatment for SARS-CoV-2, the coronavirus responsible for COVID-19 (see NCT04784897 ). Brilacidin has shown potent and consistent inhibition in vitro against coronaviruses, alphaviruses and bunyaviruses (with laboratory testing against other viruses also underway), supporting Brilacidin’s potential to be developed as a broad-spectrum antiviral. The annual global antiviral drug market is estimated to reach $44 billion by 2026.

A peer-reviewed article in Viruses supporting Brilacidin’s COVID-19 treatment potential can be accessed at the link below.

Bakovic, A.; Risner, K.; Bhalla, N. (et al). Brilacidin Demonstrates Inhibition of SARS-CoV-2 in Cell Culture. Viruses 2021, 13 , 271; https://doi.org/10.3390/v13020271 https://www.mdpi.com/1999-4915/13/2/271/

Two independent Machine Learning studies identified Brilacidin as one of the most promising inhibitors of SARS-CoV-2, the virus responsible for COVID-19, based on Brilacidin’s molecular properties. Click here to learn more.

Alerts Sign-up for Innovation Pharmaceuticals email alerts is available at: http://www.ipharminc.com/email-alerts/

About Innovation Pharmaceuticals Innovation Pharmaceuticals Inc. (IPIX) is a clinical stage biopharmaceutical company developing a world-class portfolio of innovative therapies addressing multiple areas of unmet medical need, including inflammatory diseases, cancer, infectious diseases, and dermatologic diseases.

Forward-Looking Statements: This press release contains forward-looking statements made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995 including statements concerning future drug development plans, statements regarding the antiviral capabilities and therapeutic potential of Brilacidin and its impact on SARS-CoV-2 (COVID-19) and other viruses, as well as obtaining government regulatory approvals to commence clinical testing. Other statements regarding future product developments, and markets, including with respect to specific indications, and any other statements which are other than statements of historical fact, involve risks but not limited to risks related to conducting pre-clinical studies and clinical trials and seeking regulatory and licensing approvals for Brilacidin and Kevetrin in the US and other jurisdictions; that prior test results may not be replicated in future studies and trials, uncertainties and assumptions that could cause the Company’s actual results and experience to differ materially from anticipated results and expectations expressed in these forward-looking statements. The Company has in some cases identified forward-looking statements by using words such as “anticipates,” “believes,” “hopes,” “estimates,” “looks,” “expects,” “plans,” “intends,” “goal,” “potential,” “may,” “suggest,” and similar expressions. Among other factors that could cause actual results to differ materially from those expressed in forward-looking statements are the Company’s need for, and the availability of, substantial capital in the future to fund its operations and research and development; including the amount and timing of the sale of shares of common stock under securities purchase agreements; the fact that the Company’s licensee(s) may not successfully complete pre-clinical or clinical testing and the Company will not receive milestone payments, or the fact that the Company’s compounds may not successfully complete pre-clinical or clinical testing, or be granted regulatory approval to be sold and marketed in the United States or elsewhere. A more complete description of these risk factors is included in the Company’s filings with the Securities and Exchange Commission. You should not place undue reliance on any forward-looking statements. The Company undertakes no obligation to release publicly the results of any revisions to any such forward-looking statements that may be made to reflect events or circumstances after the date of this press release or to reflect the occurrence of unanticipated events, except as required by applicable law or regulation.

INVESTOR AND MEDIA CONTACTS Innovation Pharmaceuticals Inc. Leo Ehrlich [email protected]

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Vistagen Announces Completion of Last Patient, Last Visit in Phase 2 Clinical Trial of PH94B for the Treatment of Adjustment Disorder with Anxiety

Topline results of the exploratory Phase 2 clinical study anticipated in Q1 2023

SOUTH SAN FRANCISCO, Calif. --(BUSINESS WIRE)-- Vistagen (Nasdaq: VTGN), a late clinical-stage biopharmaceutical company aiming to transform the treatment landscape for individuals living with anxiety, depression, and other central nervous system (CNS) disorders, today announced that the last patient has completed the study protocol in its Phase 2 clinical trial of PH94B for the treatment of adults experiencing adjustment disorder with anxiety (AjDA).

The exploratory Phase 2 clinical trial is a U.S. multi-center, randomized, double-blind, placebo-controlled study intended to evaluate efficacy, safety and tolerability of PH94B administered four times per day over four weeks for the treatment adjustment disorder with anxiety symptoms in adults. The primary endpoint is the change from baseline in anxiety level as measured by the Hamilton Anxiety Rating Scale (HAM-A) at the end of Week 4 of treatment with PH94B or placebo. Dr. Michael Liebowitz , a former Columbia University psychiatrist, founder of the Anxiety Disorders Clinic at the New York State Psychiatric Institute , and currently director of the Medical Research Network in New York City , is serving as Principal Investigator of the trial. Topline results are anticipated at the end of Q1 2023.

“The four-week treatment protocol for our final enrolled patient is complete. This is a major milestone for our team,” stated Shawn Singh , Chief Executive Officer of Vistagen. “Along with many other mental health challenges, the prevalence of adjustment disorder is alarming due to increasing levels of health, safety, economic and social stressors that adversely impact mental health and wellbeing. Vistagen is dedicated to developing treatments to address the escalating mental health crisis. We look forward to completing data analysis for this important study over the coming months.”

About PH94B

Vistagen’s PH94B is a first-in-class, rapid-onset investigational pherine nasal spray with a novel proposed mechanism of action (MOA) that regulates the olfactory-amygdala neural circuits of fear and anxiety and attenuates the tone of the sympathetic autonomic nervous system, without systemic distribution, potentiation of GABA-A or direct activity on CNS neurons in the brain. Vistagen is developing PH94B in a Phase 3 program for the treatment of social anxiety disorder and in an exploratory Phase 2 development program for the treatment of adjustment disorder with anxiety. Designed for intranasal administration in low microgram doses, the proposed novel MOA of PH94B is fundamentally differentiated from all currently approved anti-anxiety medications, including all antidepressants and benzodiazepines.

About Adjustment Disorder

Adjustment disorder (AjD) refers to a maladaptive emotional or behavioral response to an identifiable stressor. AjD occurs within three months of exposure to the stressor as evidenced by marked distress that is out of proportion to the socially or culturally expected reactions to the stressor, or that represents significant impairment in social, occupational or other important areas of daily functioning. A Mental Health Surveillance Study estimated prevalence of adjustment disorder at 7% in the U.S. adult population, or about 18 million adults in the U.S , in 2022. Current pharmacological treatments for AjD vary widely. Current treatments include antidepressants, benzodiazepines and buspirone, among others.

About Vistagen

Vistagen (Nasdaq: VTGN) is a late clinical-stage biopharmaceutical company aiming to transform the treatment landscape for individuals living with anxiety, depression and other CNS disorders. The Company is advancing therapeutics with the potential to be faster-acting, and with fewer side effects and safety concerns, than those that are currently available. Vistagen’s clinical-stage candidates are targeting multiple forms of anxiety and depression. PH94B and PH10 belong to a new class of drugs known as pherines, which are investigational neuroactive steroid nasal sprays designed with a novel rapid-onset mechanism of action that activates chemosensory neurons in the nasal passages and can impact the olfactory-amygdala neural circuits without systemic uptake or direct activity on CNS neurons in the brain. Vistagen is passionate about transforming mental health care and redefining what is possible in the treatment of anxiety and depression. Connect at www.Vistagen.com .

Forward Looking Statements

This press release contains certain forward-looking statements within the meaning of the federal securities laws. These forward-looking statements involve known and unknown risks that are difficult to predict and include all matters that are not historical facts. In some cases, you can identify forward-looking statements by the use of words such as “may,” “could,” “expect,” “project,” “outlook,” “strategy,” “intend,” “plan,” “seek,” “anticipate,” “believe,” “estimate,” “predict,” “potential,” “strive,” “goal,” “continue,” “likely,” “will,” “would” and variations of these terms and similar expressions, or the negative of these terms or similar expressions. Such forward-looking statements are necessarily based upon estimates and assumptions that, while considered reasonable by Vistagen and its management, are inherently uncertain. As with all pharmaceutical products, there are substantial risks and uncertainties in the process of development and commercialization and actual results or developments may differ materially from those projected or implied in these forward-looking statements. Among other things, there can be no guarantee that any of the Company’s drug candidates, including PH94B and/or PH10, or any other pherine drug candidate will successfully complete ongoing or future clinical trials, receive regulatory approval or be commercially successful. These risks, along with additional risks, are more fully discussed in the section entitled "Risk Factors" in the Company’s most recent Annual Report on Form 10-K for the fiscal year ended March 31, 2022 and in the Company’s most recent Quarterly Report on Form 10-Q for the quarter ended September 30, 2022 , as well as discussions of potential risks, uncertainties, and other important factors in our other filings with the U.S. Securities and Exchange Commission (SEC). The Company’s SEC filings are available on the SEC’s website at www.sec.gov . You should not place undue reliance on these forward-looking statements, which apply only as of the date of this press release and should not be relied upon as representing the Company’s views as of any subsequent date. The Company explicitly disclaims any obligation to update any forward-looking statements, other than as may be required by law. If the Company does update one or more forward-looking statements, no inference should be made that the Company will make additional updates with respect to those or other forward-looking statements.

last patient last visit clinical trial

View source version on businesswire.com : https://www.businesswire.com/news/home/20230110005496/en/

Investors Mark Flather Vice President, Investor Relations (650) 577-3617 [email protected]

Media Nate Hitchings SKDK [email protected]

Source: Vistagen

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last patient last visit clinical trial

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Press release, vistagen announces completion of last patient, last visit in phase 1 clinical trial of itruvone (ph10), an investigational pherine nasal spray for major depressive disorder.

U.S. Phase 1 study with newly optimized formulation intended to facilitate Phase 2B development of itruvone as a stand-alone treatment of major depressive disorder

Top line results anticipated in Q2 2023

SOUTH SAN FRANCISCO, Calif. --(BUSINESS WIRE)--Mar. 8, 2023-- Vistagen (NASDAQ: VTGN) a late clinical-stage biopharmaceutical company aiming to transform the treatment landscape for individuals living with anxiety, depression and other central nervous system (CNS) disorders, today announced that the last participant has completed the study protocol in its U.S. Phase 1 clinical trial of itruvone (PH10), the Company’s investigational pherine nasal spray for the treatment of major depressive disorder (MDD).

The primary objective of this U.S. single-center, randomized, double-blind, placebo-controlled Phase 1 study is to investigate the safety and tolerability of itruvone in healthy adult subjects. The study is intended to confirm the favorable safety profile of itruvone established in three previous clinical studies conducted in Mexico , including a published Phase 2A study of itruvone as a stand-alone treatment of MDD, as well as facilitate Phase 2B development of itruvone as a stand-alone treatment for MDD. Vistagen anticipates top line results in Q2 2023.

Shawn Singh , Chief Executive Officer of Vistagen. “Major depressive disorder continues to disrupt the lives of millions of individuals and there is clear need for safer, more effective treatments, especially treatments with potential for rapid-onset and sustained benefits without causing sexual side effects or weight gain. We anticipate this U.S. Phase 1 trial will build on itruvone’s exceptional safety and tolerability profile as demonstrated in all prior clinical studies to date.”

About Itruvone (PH10)

Itruvone (PH10) is an investigational pherine nasal spray designed with a potential rapid-onset mechanism of action (MOA) that is fundamentally differentiated from the MOA of all currently approved treatments for depression disorders. Itruvone, which is administered at microgram-level doses, is designed to engage and activate chemosensory neurons in the nasal passages connected to neural circuits in the brain that produce antidepressant effects. Specifically, itruvone’s proposed MOA involves binding to receptors of chemosensory neurons in the nasal passages that regulate the olfactory-amygdala neural circuits believed to increase the activity of the limbic-hypothalamic sympathetic nervous system and increase the release of catecholamines. Importantly, unlike all currently approved oral antidepressants and rapid-onset ketamine-based therapy (KBT), including both intravenous ketamine and intranasal ketamine, we believe itruvone does not require systemic uptake or brain penetration to produce rapid-onset of antidepressant effects, avoiding side effects and safety concerns potentially associated with rapid-onset KBT and longer acting oral antidepressants.

About Vistagen

Vistagen (Nasdaq: VTGN) is a late clinical-stage biopharmaceutical company aiming to transform the treatment landscape for individuals living with anxiety, depression and other CNS disorders. The Company is advancing therapeutics with the potential to be faster-acting, and with fewer side effects and safety concerns, than those that are currently available for treatment of anxiety and depression disorders. Several of Vistagen’s product candidates belong to a new class of drugs known as pherines, which are designed with a novel rapid-onset mechanism of action that activates chemosensory neurons in the nasal passages and can impact key neural circuits without systemic uptake or direct activity on CNS neurons in the brain. Vistagen is passionate about transforming mental health care and redefining what is possible in the treatment of anxiety and depression. Connect at www.Vistagen.com .

Forward Looking Statements

This press release contains certain forward-looking statements within the meaning of the federal securities laws. These forward-looking statements involve known and unknown risks that are difficult to predict and include all matters that are not historical facts. In some cases, you can identify forward-looking statements by the use of words such as “may,” “could,” “expect,” “project,” “outlook,” “strategy,” “intend,” “plan,” “seek,” “anticipate,” “believe,” “estimate,” “predict,” “potential,” “strive,” “goal,” “continue,” “likely,” “will,” “would” and variations of these terms and similar expressions, or the negative of these terms or similar expressions. Such forward-looking statements are necessarily based upon estimates and assumptions that, while considered reasonable by Vistagen and its management, are inherently uncertain. As with all pharmaceutical products, there are substantial risks and uncertainties in the process of development and commercialization, and actual results or developments may differ materially from those projected or implied in these forward-looking statements. Among other things, there can be no guarantee that any of Vistagen’s drug candidates, including itruvone (PH10), will successfully complete ongoing or future clinical trials, receive regulatory approval or be commercially successful. Other factors that may cause such a difference include, without limitation, risks and uncertainties relating to the Company’s ongoing clinical studies of fasedienol (PH94B), itruvone and AV-101; delays in launching, conducting and/or completing ongoing and/or planned clinical trials; fluctuating costs of materials and other resources required to conduct the Company’s ongoing and/or planned clinical and non-clinical trials; the scope of protection provided by the U.S. patents issued for any of the Company’s drug candidates will be sufficient to deter competition; market conditions; the impact of general economic, industry or political conditions in the United States or internationally; and other technical and unexpected hurdles in the development, manufacture and commercialization of the Company’s CNS drug candidates. Certain of these risks and others are more fully discussed in the section entitled "Risk Factors" in the Company’s most recent Annual Report on Form 10-K for the fiscal year ended March 31, 2022 and in the Company’s most recent Quarterly Report on Form 10-Q for the quarter ended December 31, 2022 , as well as discussions of potential risks, uncertainties, and other important factors in our other filings with the U.S. Securities and Exchange Commission (SEC). The Company’s SEC filings are available on the SEC’s website at www.sec.gov . You should not place undue reliance on these forward-looking statements, which apply only as of the date of this press release and should not be relied upon as representing the Company’s views as of any subsequent date. The Company explicitly disclaims any obligation to update any forward-looking statements, other than as may be required by law. If the Company does update one or more forward-looking statements, no inference should be made that the Company will make additional updates with respect to those or other forward-looking statements.

last patient last visit clinical trial

View source version on businesswire.com : https://www.businesswire.com/news/home/20230308005334/en/

Mark Flather Vice President, Investor Relations (650) 577-3617 [email protected]

Nate Hitchings SKDK [email protected]

Source: Vistagen

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Last patient last visit (LPLV)

Date when the last participant completes a clinical trial .

Although LPLV is often used synonymously with study completion, the latter may still include measurements and data collection without face-to-face involvement between a participant and an investigator.

The Clinical Trial Life Cycle and When to Share Data (Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risks, 2015) 

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Reneo Pharmaceuticals Announces Last Patient Last Visit in the Pivotal STRIDE Study of Mavodelpar in Primary Mitochondrial Myopathies (PMM)

Topline data results from the stride study are expected in december 2023.

October 09, 2023 07:50 ET | Source: Reneo Pharmaceuticals, Inc. Reneo Pharmaceuticals, Inc.

IRVINE, Calif., Oct. 09, 2023 (GLOBE NEWSWIRE) -- Reneo Pharmaceuticals, Inc. (Nasdaq: RPHM), a clinical-stage pharmaceutical company focused on the development and commercialization of therapies for patients with rare genetic mitochondrial diseases, announced last patient last visit (LPLV) in the pivotal STRIDE study of mavodelpar in PMM. Topline data results from the STRIDE study are expected in December 2023.

“This marks a major milestone for mavodelpar and the company. This achievement reached in the STRIDE program underscores the significant progress toward our corporate mission to bring therapies to patients with rare genetic mitochondrial diseases. We anticipate sharing topline results from the STRIDE clinical trial in December 2023,” said Gregory J. Flesher, Chief Executive Officer. “In addition, we are encouraged by the participation in the ongoing STRIDE AHEAD study, which has enrolled over 85% of eligible patients.”

Ashley Hall, Chief Development Officer, added “We anticipate completing the final steps in the STRIDE clinical process in the coming months. Subsequently, we plan to share the results of data analysis with the United States Food and Drug Administration (FDA) in the first quarter of 2024.  We expect that the STRIDE and STRIDE AHEAD studies will form the basis of a New Drug Application (NDA) to the FDA which is planned for submission in the first half of 2024 and thereafter to additional regulatory agencies.”

About STRIDE The STRIDE study is a global, randomized, double-blind, placebo-controlled pivotal Phase 2b trial of mavodelpar in adult patients with PMM due to mitochondrial DNA (mtDNA) defects. The study is designed to investigate the efficacy and safety of 100 mg mavodelpar administered once-daily over a 24-week period. The primary efficacy endpoint of the trial is the change from baseline in the distance walked during the 12-minute walk test (12MWT) at week 24. Secondary endpoints include changes from baseline in PROMIS® Short Form Fatigue 13a, Modified Fatigue Impact Scale (MFIS), Patient Global Impression of Change (PGIC), Patient Global Impression of Severity (PGIS), 30 Second Sit-To-Stand (30STS) Test, Brief Pain Inventory (BPI), 36-Item Health Survey (SF-36), Work Productivity and Activity Impairment Questionnaire: Specific Health Problem (WPAI:SHP), and Pedometer Step Count.

About STRIDE AHEAD The STRIDE AHEAD study is an open-label extension (OLE) trial outside of the United States in patients with PMM due to mtDNA defects who participated in STRIDE or the mavodelpar Phase 1b study. The study is designed to evaluate the long-term safety and tolerability of 100 mg mavodelpar administered once-daily over a 24-month period. STRIDE AHEAD was amended to allow enrollment of treatment naïve patients with PMM due to nuclear DNA (nDNA) defects.

About PMM PMM are a group of rare, genetic metabolic disorders caused by mutations or deletions in the mtDNA or nDNA. These genetic alterations hamper the ability of mitochondria to generate energy from nutrient sources, resulting in energy deficits that are most pronounced in tissues with high energy demand such as muscle, brain, and heart. The symptoms of PMM include muscle weakness, exercise intolerance, movement disorder, deafness, blindness, and droopy eyelids among others. The prognosis for these disorders ranges in severity from progressive weakness to death.

About Mavodelpar Mavodelpar (REN001) is a potent and selective peroxisome proliferator-activated receptor delta (PPARδ) agonist currently in clinical development for two rare genetic mitochondrial diseases that typically present with myopathy and have high unmet medical needs: PMM and long-chain fatty acid oxidation disorder. For additional information, please see  clinicaltrials.gov .

About Reneo Pharmaceuticals Reneo is a clinical-stage pharmaceutical company focused on the development and commercialization of therapies for patients with rare genetic mitochondrial diseases, which are often associated with the inability of mitochondria to produce adenosine triphosphate (ATP). Our lead product candidate, mavodelpar (REN001), is a potent and selective agonist of the peroxisome proliferator-activated receptor delta (PPARδ). Mavodelpar has been shown to increase transcription of genes involved in mitochondrial function, increase fatty acid oxidation, and may increase production of new mitochondria. For additional information, please see  reneopharma.com .

Forward-Looking Statements    Statements contained in this press release regarding matters that are not historical facts are “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995. Such forward-looking statements include statements regarding, among other things, the potential development, registration and commercialization of mavodelpar, the timing of topline data from the STRIDE study, the timing of the final steps in the clinical process for the STRIDE study and for sharing the results of data analysis with the FDA, the prospects of the STRIDE AHEAD study, and the potential filing and timing of an NDA to the FDA and thereafter to additional regulatory agencies . Because such statements are subject to risks and uncertainties, actual results may differ materially from those expressed or implied by such forward-looking statements. Words such as “plans,” “will,” “believes,” “anticipates,” “expects,” “intends,” “goal,” “potential” and similar expressions are intended to identify forward-looking statements. These forward-looking statements are based upon Reneo’s current expectations and involve assumptions that may never materialize or may prove to be incorrect. Actual results could differ materially from those anticipated in such forward-looking statements as a result of various risks and uncertainties, which include, without limitation, risks and uncertainties associated with Reneo’s business in general, and the other risks described in Reneo’s filings with the Securities and Exchange Commission. All forward-looking statements contained in this press release speak only as of the date on which they were made. Reneo undertakes no obligation to update such statements to reflect events that occur or circumstances that exist after the date on which they were made, except as required by law.   

Danielle Spangler  Investor Relations  Reneo Pharmaceuticals, Inc.  [email protected]

Matthew Purcell, Pharm.D. Media Inquiries  Russo Partners, LLC  [email protected]

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Operational Excellence in Clinical Trials

Ulrike Grimm, Vifor Pharma, analyses how clinical trial processes can be improved for the better

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Clinical trials have become a challenge. Few studies are completed on schedule and within the planned budget. There are plenty of reasons for that. In the past ten years:

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  • The number of study procedures has increased by 57 percent translating into higher investigative site work
  • The eligibility criteria have grown by 58 percent reflecting the search for always better defined patient populations
  • The number of Case Report Form pages has more than doubled

Nevertheless, having said that, there is still the expectation the pharmaceutical industry executes trials according to plan bringing drugs to the market as soon as possible.

Thus the question to be asked is: What is wrong? The answer is not simple but rather complex.

It all begins with the evaluation of development compounds. The value of the assets is higher the shorter the development period, since this guarantees longer patent protection, potentially less competition and earlier generation of sales.

The development plans therefore often reflect best case scenarios and disregard the realistic case. Now we can ask ourselves, how do we come up with realistic plans for clinical studies?

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I) There are several parameters that provide guidance during the preparation phase

1. Benchmarks

External benchmarks are available from several providers that have tracked past studies. In addition all studies conducted thus far in-house can be used to analyse the intervals between study milestones.

A combination of external and internal benchmarks to form a guide for studies in Europe and the US could look like this:

LPLV = Last Patient Last Visit

DBL = Data Base Lock

2. Recruitment period and recruitment plan

There are also benchmarks for recruitment periods per therapeutic area. However, I would caution to use high level, generic therapeutic area benchmarks for the recruitment period, because the study specific inclusion and exclusion criteria as well as the study procedure drive the recruitment period.

A detailed feasibility analysis should always be conducted to assess the recruitment period. Ideally this task is not fully outsourced to a CRO but also, or partially, done by the company’s own staff in order to have a detailed understanding of the availability of patients. The results of the feasibility analysis should be written down in a recruitment plan, where the following aspects are important to be considered:

  • The availability of the required patient population at the sites;
  • Implementation of referral sites;
  • Competitive studies;
  • Willingness of patients to participate in the study procedures;
  • Advertisements;
  • Patient retention;
  • Risk assessment (what could go wrong?);
  • Average recruitment speed of patients per months and site;
  • Number of countries, proposed countries;
  • Number of sites;
  • Anticipated dates for the following milestones (1. First patient, First visit; 2. Last patient, First visit; 3. Last patient, Last visit; 4. Clinical study report)

3. Overall study plan

In addition to the scope, objectives, milestones and timelines, the overall study plan should include the study budget and the resource plan.

Regarding the study budget, it is usually the sum of all offers that have been received during the bidding process for the requested services. However, how many studies have been completed without any change orders? A certain amount of buffer is usually accepted by all internal stakeholders and should be added to the planned study budget.

The analysis of the resource needs is particularly important, because often major activities of the clinical study conduct are outsourced to a CRO and the need for internal resources can easily be underestimated.

It is recommended to check the internal resource needs against recently conducted studies to have a good understanding of the company-specific situation and approach.

4. CRO management

The CRO management starts with the CRO selection process. Usually a Request for Proposal is sent to several CROs and depending on the expertise, past experience in the therapeutic area, the team, and the budget a CRO will be selected. A good relationship between the study team of the sponsor and the CRO is of key importance. Therefore the bid defense meetings provide an excellent opportunity to bring together the envisioned teams of both parties.

In recent years we have seen high staff turnover at the CRO in some studies. Thus, it is advantageous to agree on replacement policies right from the beginning.

Moreover we have made good experience with agreeing on a communication plan that should detail the ways of communication and reports, and also the ways of escalation.

II) Tracking study progress during its conduct

As mentioned earlier, a risk analysis should be done during the preparation of the clinical study. Once the service providers have been selected, it is recommended to jointly work on a contingency plan.

Knowing that 20 – 30 percent of sites recruit only up to one patient, despite thorough feasibility assessments, really calls for back-up sites, may be even back-up countries early on. The triggers of activating these additional sites should be agreed with the steering committee.

Once the study has been initiated the progress will be monitored on an ongoing basis. Study dashboards allow for oversight and could look as shown below:

Dashboard of key performance indicators for clinical studies

As soon as deviations from the plan become obvious the study teams of the sponsor and the CRO should have meetings to discuss the best ways to mitigate the risks and bring the study back on track. Early communication is much better than a "wait and see" approach.

III) Lessons learned at the end of a study

Once the study report has been finalized and the TMF is ready for archiving, comes the time for lessons learned. It is worth to take the time and have a ‘lessons learned’ workshop, before the study team members will be allocated to other studies.

All parts of the study can be looked at and evaluated:

  • What new benchmarks can be created from the study for timelines?
  • What new benchmarks can be created for external costs and internal resource needs?
  • How satisfied were we with the service providers?
  • What countries are easy/difficult to work with?
  • What sites would you work with again?

The outcome of these workshops should be made available on central places, e.g. on the intranet / central databases and managed by departments like clinical operations or clinical project management so that all study teams can benefit from it.

A thorough plan of all aspects of the clinical study will pay back in the end, by being prepared and able to pro-actively manage any risk and issues.

Close monitoring of the study progress will further enable the study teams to always be on top of any progress being made and to take action as soon as possible.

At the end of a study the ‘lessons learned’ workshops help to become better equipped for the planning of the next studies.

*Dr. Ulrike M. Grimm is the Head Global Project and R&D Alliance Management, Vice President of Vifor Pharma

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Benchmarking Protocol Deviations and Their Variation by Major Disease Categories

  • Original Research
  • Published: 04 April 2022
  • Volume 56 , pages 632–636, ( 2022 )
  • Kenneth Getz   ORCID: orcid.org/0000-0003-0568-2541 1 ,
  • Zachary Smith 1 ,
  • Ananya Jain 2 &
  • Randy Krauss 3  

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Little to no data exist quantifying and benchmarking the magnitude of protocol deviation experience.

Nearly two-dozen companies provided the Tufts Center for the Study of Drug Development (Tufts CSDD) with data on the design and the performance of 187 protocols.

The results of this working group study show that phase II and III protocols have a mean total of 75 and 119 protocol deviations, respectively, involving nearly one-third of all patients enrolled in each clinical trial. Oncology clinical trials have the highest relative mean number of protocol deviations affecting more than 40% of patients enrolled in each trial. The number of endpoints, the number of procedures per visit, and the number of countries were modestly positively associated with and predictive of, the incidence of deviations per protocol. A strong positive relationship was shown between the number of investigative sites and the number of protocol deviations.

The results of this initial study provide useful measures that sponsor companies can use to benchmark their own protocol deviation experience, identify factors most associated with protocol deviations, and determine whether remediation is warranted.

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Protocol Design and Performance Benchmarks by Phase and by Oncology and Rare Disease Subgroups

Kenneth Getz, Zachary Smith & Marcy Kravet

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Introduction

Despite their regimented structure, protocols are rarely followed exactly as planned. Widely referred to as protocol deviations—these changes are generally executed by the study staff, while the clinical trial is underway to accommodate study volunteers encountering difficulties complying with the schedule of visits or adhering to study medication administration requirements. Investigative site staff may also deviate from the protocol when facing difficulties finding eligible patients and challenges following and performing clinical and administrative procedures dictated by the protocol.

Protocol deviations are the top reason for clinical trial enforcement actions. Based on Food and Drug Administration (FDA) inspections of investigative sites, approximately one-third (30%) of all warning letters are due to the failure to follow the investigational plan [ 1 ]. This proportion is nearly twice the second most common reason: 17% of all warning letters are due to the failure of the investigative site to adequately maintain source documents [ 2 ].

Deviations from protocol procedures may be minor. A subset of all deviations, however, are more significant and may harm the integrity of the study, may put the rights and safety of study volunteers at risk, and may detract from the completeness, accuracy, and reliability of the study data [ 3 ]. Based on a cross-functional working group of pharmaceutical companies, Galuchie et al. have proposed definitions to differentiate deviations from protocol violations [ 4 ].

During the past decade, protocol deviations have received increased attention as part of a broader effort to improve protocol design and executional quality [ 5 , 6 ]. Consortia and collaborative groups have developed consensus definitions of protocol deviation types as well as frameworks to prevent and manage them. The Drug Information Association’s Good Clinical Practice and Quality Assurance community, for example, conducted an industry-wide survey resulting in common definitions and best practices for identifying, classifying, and managing protocol deviations [ 3 ]. More recently, industry consortium TransCelerate BioPharma developed a conceptual protocol deviation identification, management framework, and toolkit—incorporating risk- and issue-management principles [ 4 ].

Despite this growing attention over the past ten years, to our knowledge, little to no data exist quantifying and benchmarking the magnitude of protocol deviation experience. The purpose of this paper is to share the results of a recent study conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD). It is our hope that these results will serve as a useful baseline measure that sponsor companies can compare against their protocol deviation experience and determine if remediation may be required.

Data on protocol deviations and other protocol design characteristics were collected and reported by twenty major and mid-sized pharmaceutical companies and contract research organizations (CROs): Amgen, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, CSL Behring, Eli Lilly, EMD Serono, GlaxoSmithKline, Janssen, Merck & Co. (Kenilworth NJ), Novartis, Otsuka, Parexel, Pfizer, Roche, Sanofi, Takeda, UCB, and Veristat.

Clinical and clinical operation professionals from each participating company gathered data from a convenience sample of clinical trial protocols that had received final protocol approval between January 2013 and December 2018 and had a primary completion date or database lock date before December 31st, 2019. CROs participating in the study gathered protocol data specifically from client companies that were not represented by the other participating sponsor companies in the working group.

Each participating company was asked to select protocols representative of their current portfolio of clinical trial activity and to include protocols from each of three phases (i.e., Phase I, Phase II, and Phase III). Each participating company submitted between 6 and 21 protocols. The analysis dataset focused on traditional protocol designs and excluded master protocols and adaptive designs.

The data collection process deployed in this study followed the approach that Tufts CSDD has used to evaluate trends in, and the impact of, protocol design practice since 2008. The results of these studies have been published extensively. A number of design variables were gathered, including number and type of endpoints, number of eligibility criteria, number of distinct and total procedures performed, number of countries and investigative sites where the protocol was conducted, and number of planned study volunteer visits per month.

Clinical trial performance and quality variables were also gathered, including clinical trial milestone durations, retention rates, the number of substantial protocol amendments, and the total number of protocol deviations. Planned and actual milestone durations were assessed. The following performance and quality variable definitions informed the data collection process for this study:

Study start-up duration—days from Protocol Approval to First Patient First Visit (FPFV);

Duration to complete all first patient visits—days from First Patient First Visit to Last Patient First Visit (LPFV);

Treatment duration—days from Last Patient First Visit to Last Patient Last Visit (LPLV);

Study close-out duration—days from Last Patient Last Visit to Database Lock (DBL);

Total trial duration—days from Protocol Approval to Database Lock;

Drop-out rate—number of patients completing the clinical trial divided by the total number enrolled;

Protocol deviation—total number of changes, divergences, or departures from the study design or procedures as defined by the protocol;

Substantial protocol amendments—total number of changes made to the protocol, in all countries where it is executed, requiring suspending enrollment, obtaining internal approval followed by approval from an ethical review board or regulatory authority, and re-consenting study volunteers.

Several other measures were created for this analysis. Proportion of patients with protocol deviations were derived by dividing the total number of patients enrolled by the total number of deviations per protocol. Differences between planned and actual cycle times were also calculated using the planned and actual dates provided by companies. Protocols in the ‘LOW’ deviation cohort are those with the relative number of deviations below the median for the entire sample. The ‘HIGH’ deviation cohort had protocols with a relative number of deviations above the median for the total sample.

Data for Phase II and III protocols were combined for comparisons by major disease category given the small sample size by individual phase. Descriptive statistics including means, coefficients of variation, and medians were calculated for the number of protocol deviations per protocol and the proportion of patients with protocol deviations, by phase, and by disease category. Logistic regressions which included individual design variables (number of endpoints, number of eligibility criteria, number of unique procedures, total number of procedures, number of procedures per visit, number of countries, number of clinical sites, total number of patient visits, and number of patient visits per month) and protocol deviation cohort were conducted. Odds ratios that a protocol would be in the ‘HIGH’ deviation cohort were calculated. Correlations between the number of protocol deviations and several clinical trial outcomes were calculated: study start-up duration, duration to complete all first patient visits, treatment duration, study close-out duration, total clinical trial duration, drop-out rate, and the number of substantial protocol amendments. Finally, mean differences between planned and actual cycle times were calculated for the ‘LOW’ and ‘HIGH’ deviation cohorts.

Protocol data were stored as an excel file and saved on a secure, shared, online drive. Analysis was conducted in SAS 9.4.

A convenience sample of 187 protocols met the criteria for this analysis. Table 1 shows the distribution of protocols by phase, disease category, and Low/High number of deviations.

Means for the total number of protocol deviations, per protocol, and by phase are presented in Table 2 . Each phase III protocol has a mean number of 118.5 total deviations, involving approximately one-third of all patients participating in that protocol. Phase I protocols have the lowest mean number of deviations and involve half the proportion of patients than those observed in phase II and phase III protocols. The coefficients of variation around the mean number are very high—between 1.7 and 2.0—indicating that total deviations per protocol are widely dispersed and inconsistent.

Combined, phase II and III oncology protocols average almost 20% more total deviations than the average for non-oncology protocols at 108.8 and 91.9, respectively. Protocol deviations in combined phase II and III oncology protocols involve 47% of the total study volunteers, nearly double the proportion observed in non-oncology protocols. Rare disease indications average a lower relative number of total deviations (78.1) among a smaller proportion of study volunteers (27.7%) compared to that of non-rare disease indications (refer to Table 3 ).

Table 4 contains the results of the logistic regressions that were conducted. It contains the odds ratio that a protocol will be in the ‘HIGH’ deviation cohort, and the p -value of the individual design variable. 5 of the 9 variables tested were significant (endpoints, eligibility criteria, distinct procedures, countries, and sites) indicating that as each of these design variables increased, the odds ratio that a protocol would be in the ‘HIGH’ deviation cohort also increased. Total procedures, procedures per visit, total visits, and visits per month were not found to significantly affect this odds ratio.

Table 5 summarizes the correlations between protocol deviations and clinical trial outcomes. The incidence of protocol deviations was significantly, positively correlated with all clinical trial milestone durations except for study start-up and study close-out. The duration to complete all first patient visits (First Patient First Visit—Last Patient First Visit), the overall treatment duration (First Patient First Visit—Last Patient Last Visit), and the total clinical trial duration from protocol approval to database lock showed weak but significant positive correlations (0.283, 0.342, and 0.323, respectively) with the number of protocol deviations per protocol.

The results of this study present baseline measures of the mean total number of protocol deviations per protocol by phase and by disease category. Each phase II and III protocol has a total of 75 and 119 protocol deviations, on average, involving nearly one-third of all patients enrolled in each clinical trial. Oncology clinical trials have the highest relative mean number of protocol deviations affecting more than 40% of patients enrolled in each trial. This finding is consistent with other Tufts CSDD studies that have demonstrated the high relative burden for study volunteers participating in clinical trials targeting cancer-related illnesses [ 7 ].

A relationship between select protocol design complexity variables and the incidence of protocol deviations was observed. The number of endpoints and the number of procedures per visit were modestly positively associated with and predictive of, the incidence of deviations per protocol. Adjustments to these select design variables may play a role in preventing protocol deviations and in minimizing their risk to the study and data integrity.

Two operational variables were also positively associated with protocol deviations. The number of countries showed a modest relationship. A positive relationship was also shown between the number of investigative sites and the number of protocol deviations suggesting that decisions and behaviors that diverge from the investigational plan may be a function of variation in investigative site personnel training, site infrastructure, operating environment, and culture. Further examination is needed to understand this insight and its implications (Table 4 ).

It is not surprising that the incidence of protocol deviations was significantly and positively correlated with all clinical trial milestone durations except for study start-up and close-out. Protocol implementation burden is generally low during the study initiation process. This burden, however, for both study staff and study volunteers, becomes more pronounced as these parties comply with protocol implementation requirements over time.

Protocols with a ‘HIGH’ number of deviations above the mean generally had actual timelines closer to, or better than planned durations compared to protocols with a ‘LOW’ number of deviations (Table 6 ). Timelines for the ‘HIGH’ protocol deviations subgroup may have had their original planned timelines updated or revised leading up to the ‘actual’ start date [ 8 ].

Protocols with a ‘HIGH’ number of deviations were also more complex (e.g., a higher relative number of endpoints, procedures, countries, and investigative sites) and were expected to encounter delays. Because of this, the timelines may have been set with additional time built into the original plan. This would explain why the protocols in the ‘HIGH’ cohort often appeared to perform closer to, or better than, plan.

This study has several limitations. The data are based on a convenience sample of protocols arbitrarily selected by 20 participating companies. In addition, recognizing the challenge of gathering this data, the results derive from a relatively small sample of only 187 protocols and should be interpreted with some caution.

Future research will look at the root causes of protocol deviations and how to address them. Future research will also look at deviations with more granularity to understand the incidence and impact of minor and major deviations. Whereas some deviations may improve participation convenience and clinical trial executional feasibility, other deviations may pose substantially greater risk to study volunteer rights and safety and to the quality and integrity of the clinical trial data.

Conclusions

The results of this initial study provide useful measures that sponsor companies can begin to use to benchmark their own protocol deviation experience and determine whether remediation is warranted. Given anecdotal reports on the rapid growth of protocol deviations during the COVID-19 pandemic, when the majority of protocols transitioned to virtual and remote patient participation and data collection, this study also provides a valuable pre-pandemic baseline measure to evaluate ongoing and post-pandemic protocol deviation experience and its impact.

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Acknowledgements

The authors wish to thank the companies that participated in this working group study: Amgen, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, CSL Behring, Eli Lilly, EMD Serono, GlaxoSmithKline, Janssen, Merck, Novartis, Otsuka, Parexel, Pfizer, Roche, Sanofi, Takeda, UCB, and Veristat. In addition, the authors thank Michael Wilkinson, formerly at Tufts CSDD, for his assistance on this project.

Tufts CSDD received grant funding from the participating working group companies to cover staff time on this study.

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KG, Tufts CSDD, contributed to all four aspects (substantial contribution to conception, design, analysis, and interpretation; drafting and revising the work; final approval of the version to be published; and agreement to be accountable for all aspects in ensuring accuracy and integrity of the work). ZS, Tufts CSDD, contributed to all four aspects; AJ, Biogen, made substantial contribution to conception, design, analysis, and interpretation; RK, Merck & Co., made substantial contribution to conception, design, analysis, and interpretation and assisted in drafting and revising the work.

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Correspondence to Kenneth Getz .

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Kenneth Getz, Tufts CSDD, has nothing to disclose. Zachary Smith, Tufts CSDD, has nothing to disclose. Ananya Jain, Biogen, declares that he is an employee and has financial holdings in the company. Randy Krauss, Merck & Co., declares that he is an employee and has financial holdings in the company.

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Getz, K., Smith, Z., Jain, A. et al. Benchmarking Protocol Deviations and Their Variation by Major Disease Categories. Ther Innov Regul Sci 56 , 632–636 (2022). https://doi.org/10.1007/s43441-022-00401-4

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DOI : https://doi.org/10.1007/s43441-022-00401-4

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Interview: The major changes AI will bring to the clinical landsacpe in 2024

02-Jan-2024 - Last updated on 02-Jan-2024 at 16:44 GMT

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As we head into 2024, Raj Indupuri, CEO at eClinical Solutions expects we’ll see major changes to the clinical trial landscape. We put some questions to him, to find out exactly where he thinks this part of the industry is headed.

How has rapid technology adoption, particularly AI, impacted clinical trials over the last year? ​

In 2023, we witnessed the rapid adoption of innovative technologies in life sciences; the biggest one being artificial intelligence (AI), which has proven to play a critical role in supporting modern data management. The volume and variety of clinical trial data increased significantly in recent years, with the average phase 3 trial now generating over three million data points. Even the most comprehensive data review strategies leave room for issues, leading to costly and time-consuming errors and necessitating the evolution of traditional data management approaches. AI-enabled data review capabilities for data managers and clinical data reviewers have helped to ensure data integrity in a more efficient, scalable way.

Other benefits of using AI in this way include increasing productivity – when many clinical teams face increased pressure to do more with fewer resources – and optimizing time to value. As the clinical data ecosystem evolves, detecting anomalous data becomes more complex and time-consuming. AI has become an excellent tool for optimizing data review processes and decreasing cycle times.

As AI continues to mature and companies define and refine their AI use cases, more adoption and benefits will be realized over time. Rapid tech advancements, macro trends, and the current industry state are putting more pressure on clinical development to be agile, fail fast, and be technology-first and data-driven. AI will play a critical role, and companies will need to adopt or be left behind.

What major changes do you anticipate will happen for clinical trials next year? ​

As we head into 2024, in addition to the continued acceleration of technology advancements, I expect to see changes in how digital tools are adopted for the conduct of modern trials.

As part of our continued life sciences digital transformation, I anticipate a move towards EDC-free digital trials. The potential of electronic health record (EHR) data directly integrating with other data acquisition applications and data infrastructure would phase out the need for EDC, enabling improved patient experiences and alleviating burdens on research sites.

Simultaneously, I see our industry moving beyond the hype surrounding DCTs. We’re recognizing that DCT components are really part of the natural evolution towards digitalization of trials, rather than their own separate segment.

Can you explain the concept of EDC-free digital trials and how EMR/EHR might play a crucial role in this shift? ​

When EDC was introduced, now over 20 years ago, the promise of EDC was to digitize and create better experiences. The intent was seamless acquisition and faster access to data for efficient analysis and improved outcomes. Industry adopted, and EDC did eliminate labor-intensive paper-based processes. It reduced errors associated with paper processes, making it better for data handling and data quality. However, EDC created other processes and overheads at the same time, adding new burdens for sites. The pain points were not completely solved. We ended up moving paper-based processes to electronic, web-based systems, but more inefficiencies impacted sites. The cost, resources and time for EDC processes are expensive and didn’t live up to the efficiency promise.

For the last decade plus our industry has been trying to solve that challenge. Meanwhile, eSource and eCOA have been increasing as data sources direct from patients, including external data, biomarkers, genomics, and more. The data environment is much more complex than when EDC was envisioned. The majority of data today comes from external data sources and not from EDC, which was never intended to handle such data diversity. Instead, we can bring those external data sources directly into a modern data infrastructure to eliminate silos and have data in a central source of truth for more rapid analysis and streamlined data handling, despite the increasing complexity. The reduction in data coming from EDC also lessens that double data entry workload for sites.

The shift towards direct integration of EHR data has the potential to bring meaningful and long-awaited efficiencies for clinical research. Because of recent advances in technology, we’re at a point where machine learning and AI can also be used to extract data and connect different systems, leveraging the underlying modern data infrastructure capable of ingesting, storing, and analyzing the complex data streams of modern trials. Bringing in EHR data and minimizing the dependency on EDC will help the industry realize the original streamlined vision of data handling while also tackling the mounting data challenges created by the industry’s rapid innovation.

I expect we’ll see EDC-free trials within 1-2 years, unleashing the potential for groundbreaking efficiency improvements through enhanced data sharing and reduced fragmentation. The past five years of innovation contributed to increased fragmentation of digital tools, but tech innovation has set the foundation for a new era characterized by streamlined processes, reduced friction, and the collaboration power of AI. Seamlessly connected data streams are essential to scale and power tomorrow’s breakthroughs in modern digital trials.

What challenges or obstacles might be associated with the transition to EDC-free digital trials, and how can these be addressed? ​

This is a pivotal time for our industry, and addressing the challenges that come with the transformation to EDC-free digital trials will be necessary to realize the desired benefits. Obstacles may include:

  • Data standardization – ​Diverse data formats and standards across different EMR/EHR systems may hinder seamless integration, not to mention that integrating disparate data sources and systems can be complex, time-consuming, and potentially pose interoperability challenges.
  • Data quality and accuracy ​ – The ability to access vast, high-quality data in real-time for high performance of AI/ML models is imperative.
  • Infrastructure costs ​ – Upgrading or establishing new digital trial infrastructure involves upfront costs and investing in the future.
  • Change management ​– Change management can be unintentionally minimized during new technology implementation, but having a strategy promotes successful adoption. This includes leadership buy-in, building champions, communication and upskilling. Focus on how experiences will change and the problems that will be solved. Change management is an ongoing effort that gains momentum as anticipated value is achieved.
  • Regulatory compliance – ​Adhering to evolving regulatory requirements for digital data in clinical trials and for AI will be paramount. Data security and privacy will continue to be top priorities.
  • Workforce knowledge and skills ​ – Having the proper training can ensure more effective processes, as long as those working with these tools are knowledgeable in digital and AI technology.
  • ‘Human in the Loop’ strategy ​– While AI may alleviate a lot of the workload, human oversight is still imperative to ensure accuracy. Training and building trust in AI models is key.

Addressing these challenges requires collaboration from stakeholders across healthcare and research. Initiatives such as data sharing for AI applications and intelligence, regulatory changes and data standards can enable our industry to embrace technological advancement. The transition to EDC-free digital trials will pave the way for more efficient, patient-centric, and data-driven clinical research.

You mention there will be a move beyond the hype of decentralized clinical trials (DCTs) and that DCTs were just a natural evolution towards digital trials. Why do you suggest that it does not need its own category? ​

DCTs have been a trending industry topic, gaining momentum during the pandemic. While a lot was learned during this period of DCT hype, the term was unnecessarily a buzzword. Whether you call them DCTs, virtual trials or patient-centric trials, we have been talking about this for the last decade. The objective is to bring research to patients and collect data directly from them, whether that is data collection through apps or devices or reaching patients directly with mobile health units and telehealth. Then we started talking about this shift toward DCTs, and there has been a lot of hype around the term. In reality, this was bound to happen. The approaches categorized as DCTs were really part of the natural progression toward digital trials.

The modern clinical trial will connect and collaborate with patients in new ways. Biopharma companies are recognizing that DCT is not a separate initiative or strategy, and we’re seeing companies with recently created DCT teams dismantling or moving these DCT teams into their core clinical trial teams. Many of the beneficial aspects of DCTs we saw accelerate in recent years will continue and will accelerate further, but it will be as part of a modern clinical trial rather than a separate type of DCT trial implementation.

Patient-centric, tech-driven approaches must also factor in what patients and sites want from a digital trial. Hybrid models still prevail, and the industry is finding the right balance. The movement to modern trials is not only about data quality, cost and efficiency – but about taking advantage of digital technologies when and where it promotes our shared industry goals for patient-focused, inclusive research that reduces, not adds to, the demands on sites and patients.

Only then can we call modern trials successful.

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    SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)-- Vistagen (Nasdaq: VTGN), a late clinical-stage biopharmaceutical company aiming to transform the treatment landscape for individuals living with anxiety, depression, and other central nervous system (CNS) disorders, today announced that the last patient has completed the study protocol in its Phase 2 clinical trial of PH94B for the treatment of ...

  15. PDF ClinicalTrials.gov Results: an End of Study Deliverable ...

    For applicable clinical trials, basic results must be posted within 12 months of the Last Patient Last Visit (LPLV) for the primary endpoint. If the primary endpoint occurs before the end of the study, then basic results must be posted twice, once within 12 months of the primary endpoint LPLV and again within 12 months of the study LPLV.

  16. Reneo Pharmaceuticals Announces Last Patient Last Visit in

    Reneo is a clinical-stage pharmaceutical company focused on the development and commercialization of therapies for patients with rare genetic mitochondrial diseases, which are often associated ...

  17. Operational Excellence in Clinical Trials

    LPLV = Last Patient Last Visit DBL = Data Base Lock 2. Recruitment period and recruitment plan There are also benchmarks for recruitment periods per therapeutic area.

  18. Last Patient, Last Visit Completed in RegeneRx Phase 3 Dry Eye Clinical

    ROCKVILLE, Md., Nov. 9, 2020 /PRNewswire/ -- RegeneRx Biopharmaceuticals, Inc. (OTCQB: RGRX) ("RegeneRx"), a clinical-stage drug development company focused on tissue protection, repair and...

  19. Glossary of Clinical Trial Terms

    A clinical trial where groups of volunteers are administered two or more interventions in a specific order. For example, a "two-by-two" cross-over trial design is where one group receives drug A at the beginning of the trial and then receives drug B for the rest of the trial. In the second group, participants receive drug B first and then drug A.

  20. AriBio Co., Ltd. Announces Last Patient Last Visit in Phase 2 Clinical

    SEONGNAM, South Korea--(BUSINESS WIRE)-- AriBio Co., Ltd., a clinical-stage biopharmaceutical company based in South Korea, announced today, 21 st of January 2021, the completion of last patient last visit in a Phase 2 study of AR1001.AR1001 is a first-in-class, orally dosed investigational drug for mild to moderate Alzheimer's disease. A total of 210 patients were enrolled, and 171 (81.4% ...

  21. Benchmarking Protocol Deviations and Their Variation by ...

    The duration to complete all first patient visits (First Patient First Visit—Last Patient First Visit), the overall treatment duration (First Patient First Visit—Last Patient Last Visit), and the total clinical trial duration from protocol approval to database lock showed weak but significant positive correlations (0.283, 0.342, and 0.323 ...

  22. PDF Using Study Metrics to Monitor Several Aspects of Clinical Studies

    throughout the length of the clinical trial can be done by looking at the number of IMV as a portion of expected total IMVs. ... date for last patient/last visit (LPLV) at each site, the CTL can work with the CRAs on the logistics of scheduling the close-out visits. Table 1. Site selection, qualification, and monitoring

  23. Last Patient, Last Visit Definition

    Last Patient, Last Visit means with respect to the relevant clinical trial the final visit to the trial site, to the treating physician for the clinical trial subject or such other final requirement for the last patient on study drug in that clinical trial, required by the protocol for that clinical in order for the database to be locked.

  24. Stuart Therapeutics Announces First Patient, First Visit in ...

    STUART, Fla., Dec. 29, 2023 /PRNewswire/ -- Stuart Therapeutics, Inc. ("Stuart"), a clinical stage biopharmaceutical company conducting research and development of unique extracellular matrix-targeting peptide therapeutics for ophthalmic diseases, today announced the First Patient First Visit (FPFV) for the company's Phase 3 clinical trial of ST-100 (vezocolmitide), in Dry Eye Disease patients.

  25. 10 clinical trials to watch in the first half of 2024

    In early 2024, Vertex will release results from a pair of placebo-controlled studies and a third, single-arm trial, in different forms of acute pain. Late-stage studies in chronic pain are following. The financial implications for Vertex are enormous, with some analysts estimating VX-548 could generate more than $10 billion in peak annual sales ...

  26. The major changes AI will bring to clinical trials in 2024

    Whether you call them DCTs, virtual trials or patient-centric trials, we have been talking about this for the last decade. The objective is to bring research to patients and collect data directly from them, whether that is data collection through apps or devices or reaching patients directly with mobile health units and telehealth.