Quantifying the feasibility of shortening clinical trial duration using surrogate markers

The amount of time and resources invested in bringing novel therapeutics to market has increased year over year with fewer successful treatments reaching patients. In the lifecycle of drug development, the clinical phase is a major contributor to this decreasing efficiency in the development of clinical trials. One major barrier to the successful execution of a randomized control trial (RCT) is the attrition of patients who no longer participate in a trial either following enrollment or randomization. To address this problem, we have assembled a unique dataset by integrating multiple public databases including ClinicalTrials.gov and Aggregate Analysis of ClincalTrials.gov (AACT) to assemble a trial sponsor-independent dataset. This data spans 20 years of clinical trials and over 1 million patients (3,175 cohorts consisting of 1,020,085 patients and 79 curated features) in the respiratory domain and enabled a data-driven approach to identify top features influencing patient attrition in a trial. Top Features included Duration of Trial, Duration of Treatment, Indication, and Number of Adverse Events. We evaluated multiple machine learning models and found the best performance on the Test Set with Random Forest (Test subset: n=637 cohorts; RMSE 6.64). We envisage that our work will enable clinical trial sponsors to optimize trial run time by better anticipating and correcting for potential patient attrition using patient-centric strategies to improve patient engagement, thus enabling new therapies to be delivered to patients more quickly.

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Psilocybin for depression: Considerations for clinical trial design

Journal of Psychedelic Studies ◽

10.1556/2054.2019.026 ◽

2019 ◽

Vol 3 (3) ◽

pp. 269-279

Author(s):

Kelley C. O’Donnell ◽

Sarah E. Mennenga ◽

Michael P. Bogenschutz

Keyword(s):

Clinical Trial ◽

Trial Design ◽

Depressive Symptomatology ◽

Specific Effect ◽

Clinical Trial Design ◽

Depressive Illness ◽

Trial Methodology ◽

Trial Duration ◽

Clinical Trial Methodology ◽

Psychedelic Drugs

Background and aims Given the enormous global burden of depressive illness, there is an urgent need to develop novel and more effective treatments for major depressive disorder (MDD). Recent findings have suggested that psychedelic drugs may have a role in the treatment of depressive symptoms, and a number of groups are in the process of developing protocols to study this question systematically. Given the subjective quality of both the psychedelic experience and depressive symptomatology, great care must be taken when designing a protocol to study the clinical efficacy of psychedelic drugs. This study will discuss many factors to consider when designing a clinical trial of psilocybin for MDD. Methods We provide a thorough review of pertinent research into antidepressant clinical trial methodology and review practical considerations that are relevant to the study of psychedelic-assisted treatment for depression. Results We discuss participant selection (including diagnostic accuracy, exclusion criteria, characteristics of the depressive episode, and the use of concurrent medications), study interventions (including dosing regimens, placebo selection, non-pharmacological components of treatment, and the importance of blinding), trial duration, outcome measures, and safety considerations. Conclusions Careful and transparent study design and data analysis will maximize the likelihood of generating meaningful, reproducible results, and identifying a treatment-specific effect. Meeting the highest standards for contemporary trial design may also broaden the acceptance of psychedelic research in the scientific community at large.

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Analysis of costs and strategies for using academic research in a private dental college to develop commercially viable products

10.1101/2020.06.02.129338 ◽

2020 ◽

Author(s):

Rampalli Viswa Chandra ◽

Devaraju Rama Raju

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Product Development ◽

Negative Impact ◽

Academic Research ◽

Research Projects ◽

Trial Duration ◽

Cycle Times ◽

Surgical Devices

ABSTRACTBackground & objectivesThe study had two aims. 1) Analysis of research projects done in our institution from 2014-2019 to identify products with a potential for commercialization and 2) To understand the effect of product-development variables on research projects to improve the quality of future commercialization-oriented trials.Methods338 clinical trials were grouped into 188 projects under the headings irrigants, diagnostic devices, surgical devices, biomaterials and gels. Trials per project, capital, material costs, labour and the cycle times per trial were calculated. To understand the effect these variables, five hypotheses were generated to test whether greater number of trials, successes, higher capital, more investigators per trial and a longer trial duration will result in a product worthy of commercialization.Results22 projects had products with a potential for commercialization. Except labour and cycle time (p>0.05), all variables showed significant differences across all projects. Three products were identified as having potential for actual commercialization. It was observed that greater number of trials (χ2=4.6793; p=0.030528) and successes (χ2=20.8134; p<0.00001) in a project along with a higher capital (χ2=12.2662; p=0.000461) will generate a product worthy of commercialization.Interpretation & conclusionsThe results seem to suggest that in trials for commercialization, emphasis must be placed on implementing multiple, well-designed clinical trials on a device or product to successfully identify whether it is commercialization-worthy or not. Due attention must be given to the financial aspects of the projects as deficiencies may result in negative impact on the flow and outcomes of a clinical trial.

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A phase III clinical trial of adjuvant chemotherapy versus chemoimmunotherapy for stage IB-IIIA completely resected non-small cell lung cancer (NSCLC) patients nadim-adjuvant: New adjuvant trial of chemotherapy versus chemoimmunotherapy.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.tps8581 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. TPS8581-TPS8581

Author(s):

Virginia Calvo ◽

Manuel Domine ◽

Ivana Sullivan ◽

Jose-Luis Gonzalez-Larriba ◽

Ana Laura Ortega ◽

...

Keyword(s):

Lung Cancer ◽

Clinical Trial ◽

Adjuvant Chemotherapy ◽

Adjuvant Treatment ◽

Disease Free Survival ◽

Disease Recurrence ◽

Primary Objective ◽

Phase Iii ◽

Trial Duration ◽

Open Label

TPS8581 Background: The results of current studies are considered acceptable evidence to support the hypothesis of efficacy of the proposed combination of immunotherapy with chemotherapy (CT-IO) in patients with NSCLC stages Ib-IIIA candidates for adjuvant treatment. Methods: This is an open-label, randomised, two-arm, phase III, multi-centre clinical trial. Primary objective and endpoint: The primary objective is disease free survival (DFS) defined time from randomization to the earliest event defined as disease recurrence, any new lung cancer (even in the opposite lung), or death from any cause at any known point in time Sample size: 210 patients NSCLC stages Ib-IIIA (Experimental Arm (Adjuvant Chemotherapy-Inmunotherapy + maintenance adjuvant Inmunotherapy): 105 patients, Control Arm (Adjuvant Chemotherapy): 105 patients Treatment Patients randomised to the experimental arm will receive Nivolumab 360mg + Paclitaxel 200mg/m2 + Carboplatin AUC5 for 4 cycles every 21 days (+/- 3 days) as adjuvant treatment followed by maintenance adjuvant treatment for 6 cycles with Nivolumab 480 mg Q4W (+/- 3 days). Patients randomized to the control arm will receive Paclitaxel 200mg/m2 + Carboplatin AUC5 for 4 cycles every 21 days (+/- 3 days) followed by 2 observation visits. Total trial duration: 6.5 years, 3.5 years of recruitment, 1 year of adjuvant treatment or observation and 2 years of follow up. The start date was January 2021. The estimated primary completion date is June 2027. Clinical trial information: NCT04564157.

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CURRENT DEFINITIONS OF PERIPROCEDURAL MYOCARDIAL INFARCTION ARE NOT SURROGATE MARKERS FOR CATHETERIZATION LAB QUALITY OR CLINICAL TRIAL END POINTS

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(14)60019-x ◽

2014 ◽

Vol 63 (12) ◽

pp. A19

Author(s):

Nevin Baker ◽

Ricardo Escarcega Alarcon ◽

Michael Lipinski ◽

Sa'ar Minha ◽

Marco Magalhaes Pereira ◽

...

Keyword(s):

Myocardial Infarction ◽

Clinical Trial ◽

Surrogate Markers ◽

End Points ◽

Periprocedural Myocardial Infarction

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Generalized Competing Event Models Can Reduce Cost and Duration of Cancer Clinical Trials

JCO Clinical Cancer Informatics ◽

10.1200/cci.17.00124 ◽

2018 ◽

pp. 1-12

Author(s):

Kaveh Zakeri ◽

Neil Panjwani ◽

Ruben Carmona ◽

Hanjie Shen ◽

Lucas K. Vitzthum ◽

...

Keyword(s):

Prostate Cancer ◽

Clinical Trial ◽

Clinical Trials ◽

Head And Neck ◽

Sensitivity Analyses ◽

Risk Scores ◽

Trial Duration ◽

Trial Efficiency ◽

Risk Of Cancer ◽

Trial Cost

Purpose Generalized competing event (GCE) models improve stratification of patients according to their risk of cancer events relative to competing causes of mortality. The potential impact of such methods on clinical trial power and cost, however, is uncertain. We sought to test the hypothesis that GCE models can reduce estimated clinical trial cost in elderly patients with cancer. Methods Patients with nonmetastatic head and neck (n = 9,677), breast (n = 22,929), or prostate cancer (n = 51,713) were sampled from the SEER-Medicare database. Using multivariable Cox proportional hazards models, we compared risk scores for all-cause mortality (ACM) and cancer-specific mortality (CSM) with GCE-based risk scores for each disease. We applied a cost function to estimate the cost and duration of clinical trials with a primary end point of overall survival in each population and in high-risk subpopulations. We conducted sensitivity analyses to examine model uncertainty. Results For the purpose of enriching subpopulations, GCE models reduced estimated clinical trial cost compared with Cox models of ACM and CSM in all disease sites. The relative cost reductions with GCE models compared with ACM and CSM models, respectively, were −68.4% and −14.4% in prostate cancer, −38.8% and −18.3% in breast cancer, and −17.1% and −4.1% in head and neck cancer. Cost savings in breast and prostate cancers were on the order of millions of dollars. The GCE model also reduced relative clinical trial duration compared with CSM and ACM models for all disease sites. The optimal risk score cutoff for clinical trial enrollment occurred near the top tertile for all disease sites. Conclusion GCE models have significant potential to improve clinical trial efficiency and reduce cost, with a potentially large impact in prostate and breast cancers.

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