Limitations of adaptive clinical trials

Using real-world data to accelerate the search for long COVID therapies

Long COVID, a spectrum of symptoms and syndromes that can develop after SARS-COV-2 infection, can significantly affect patients' health, quality of life and impact their ability to productively function in society. There is currently no approved therapy for Long COVID and there is an urgent need for rigorous clinical trials to find such treatments. Although research into the pathophysiology of Long COVID is advancing, investigations into treatment for patients remain underfunded and, as a result, understudied. Owing to the urgency of the Long COVID pandemic and as a research collaborative across a diversity of biomedical innovation value propositions, we are calling for a new approach that parallelizes pathophysiologic and therapeutic research into this condition, leveraging patient-centered research and real-world data to generate hypotheses to assess the effectiveness of existing FDA approved drugs. Accelerated discovery of therapeutics for Long COVID can then be confirmed through efficient and cost-effective adaptive platform clinical trials.

Targeted combination therapies in oncology: challenging regulatory frameworks designed for monotherapies in Europe

The pharmaceutical value chain, including clinical trials, pricing, access, and reimbursement, is designed for classical monotherapies. Although there has been a paradigm shift that increases the relevance of targeted combination therapies (TCTs), regulation and common practice have been slow to adapt. We explored access to 23 TCTs for advanced melanoma and lung cancer as reported by 19 specialists from 17 leading cancer institutions in nine European countries. We find heterogeneous patient access to TCTs between countries, differences in country-specific regulations, and differences in the clinical practice of melanoma and lung cancer. Regulation that is better tailored to the context of combinational therapies can increase equity in access across Europe and promote an evidence-based and authorized use of combinations.

Statistical Considerations for Trials in Adjuvant Treatment of Colorectal Cancer

The design of the best possible clinical trials of adjuvant interventions in colorectal cancer will entail the use of both time-tested and novel methods that allow efficient, reliable and patient-relevant therapeutic development. The ultimate goal of this endeavor is to safely and expeditiously bring to clinical practice novel interventions that impact patient lives. In this paper, we discuss statistical aspects and provide suggestions to optimize trial design, data collection, study implementation, and the use of predictive biomarkers and endpoints in phase 3 trials of systemic adjuvant therapy. We also discuss the issues of collaboration and patient centricity, expecting that several novel agents with activity in the (neo)adjuvant therapy of colon and rectal cancers will become available in the near future.

A review of phase II trial designs for initial marker validation

Phase II clinical trials aim to identify promising experimental regimens for further testing in phase III trials. In this review article, we focus on phase II designs for initial predictive biomarker validation to determine if a drug should be developed for an unselected patient population or for a biomarker-defined patient subset only. Several prospective designs for biomarker-directed therapy have been proposed, differing primarily in the study population, or randomization scheme, or both. The design choice is driven by scientific rationale, marker prevalence, strength of preliminary evidence, assay performance, and turn-around times for marker assessment. The enrichment design is most appropriate when compelling preliminary evidence suggests treatment benefit in only certain marker-defined subgroups, the all-comers design is useful when preliminary evidence regarding treatment effects in marker subgroups is unclear, and adaptive designs have the most potential in the setting of multiple treatment options and multiple marker-defined subgroups. We recently proposed a 2-stage phase II design that has the option for direct assignment (i.e., stop randomization and assign all patients to the experimental arm in stage 2) based on interim analysis (IA) results. This design not only recognizes the need for randomization but also acknowledges the possibility of promising but inconclusive results after pre-planned IA. Simulation studies demonstrated that the direct assignment-option design has minimal power loss, marginal increase in type I error rates, and reasonable robustness to population shift effects. Systematic evaluation and implementation of these design strategies in the phase II setting are essential for accelerating the clinical validation of biomarker guided-therapy.