Protocol Development #55
In this issue, there's a bit of everything and something for everyone. Topics include:
Patient Engagement
[Whitepaper] Gorman et al published Empowering Clinical Research Sites and Sponsors in the Patient-centric Era that highlights the plight of research sites. As Kerry Gorman puts it:
"We’re in this period of flux regarding the evolution of clinical trials. Sites have told us over and over again they want to have a seat at the table when it comes to designing research trials. They know what will work best, not only for the site industry in general but for a particular trial for their particular site."
To compound this, the authors discuss the further impact that DCT implementation in the wake of COVID has disrupted research - an abundance of fragmented, non-integrated, and splintered technology solutions in combination with a lack of personnel to support these infrastructural changes. IQVIA's response to these challenges involve a consolidated technology platform? (integrated patient technology) and recommend that sponsors engage sites on an entire portfolio of multiple studies in order to benefit from consistency and trust.
[Magazine] Elizabeth Tilley Hinkle published Lessons learned from oncology research: Put patients at the center and embrace new tools and strategies that also calls for patient engagement to drive protocol development for patient-centric studies. Elizabeth also touches on other lessons learned topics including the use of technology, biomarkers, adaptive designs, and more sophisticated collaborative networks, such as platform studies, that share data on developing treatments. If you work routinely with oncology protocols - some of these should be familiar, certainly from my perspective adaptive designs and biomarkers are hallmark obstacles particularly for early product development.
Diversity, Equity & Inclusion
[Magazine] Elizabeth Tilley Hinkle published National Academies report urges greater inclusion of pregnant participants in clinical research that summarizes the recent NASEM report that discusses the inclusion of pregnant participants and how researchers need to move away from the protectionist ethic towards inclusive practice; after all, once a product is approved, it can be prescribed to pregnant people or those with childbearing potential - prescribing practice that is not monitored in the same way as for clinical studies. Easy right? Elizabeth does provide some background on why protectionist approaches have been the preferred method to date - safety, liability, complexity, legality all play a role in concern for enrolling a vulnerable population. With over 70% of pregnant patients taking one or more prescription medications in the US, there is a logical justification for including the population in studies for products that are likely to be used by such a population in the future. Should I expect changes in eligibility criteria overnight? Unlikely. It'll take a long time for Sponsors and investigators to become comfortable with such an approach.
Regulations & Guidance
[Article - Commentary] Marjorie Zettler published FDA Issues New Draft Guidances On Cancer Clinical Trial Eligibility Criteria that highlight the three new FDA guidance documents on oncology eligibility criteria - covering washout periods and concomitant medication, performance status, and laboratory values. The authors also summarized recent evidence supporting the relaxation of strict eligibility criteria. Citing a recent study in NEJM, the authors increased eligibility from 48% to 78% in a sample of oncology patients by broadening criteria including eGFR, ECOG performance status, creatinine clearance, and hemoglobin.
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Clinical Study Design
[Article - Methodology] Arnold et al published Application of the target trial emulation framework to external comparator studies that touches on how to approach external comparator (EC) studies using a target trial emulation (TEE) ?framework to improve the design and analysis of EC studies. Whether you think this applies to protocol development or not will depend on past experience and what expectations you have on study design. Certainly, a well-designed study outline for a study with an EC arm should have a clear description on what is feasibly and the justification for why such an EC has been selected. In my experience, this is rarely the case and many study teams want to generate a protocol with the EC arm in name only and to be specified later. This resource provides a good overview on the topic and can help study teams understand what details they'll need to include in the protocol or elsewhere.
[Article - Methodology] Niu et al published Application of estimand framework to the design and analysis of multi-regional clinical trials that provides an overview of defining estimands in the context of MRCTs. The authors break down estimands into their 5 components and discuss each in detail. In section 2, the authors focus on primary and key secondary objectives and so the estimand discussion focuses on expected commonalities between regions (rather than differences). In section 3, there's a regional focus that includes sensitivity estimators and regional estimation consistency. In section 4, RAISE and LEADER are used as case studies that can help tie real-world examples to theory.
[Article - Case Study] Zaragoza Domingo et al published Methods for Neuroscience Drug Development: Guidance on Standardization of the Process for Defining Clinical Outcome Strategies in Clinical Trials that tackles a known obstacle for neuroscience studies - high failure rates due to challenges in defining and meeting achievable outcomes. The article presents a 7-step standard process for defining clinical outcome strategies. How can this be useful for protocol development? As with many topics, having the appropriate source material can be a significant differentiator for a good vs bad protocol. A standard outcome research plan would do wonders for framing the purpose of the study and the justification for its component as it would enable all readers and reviewers to understand the logic and evidence supporting the objectives, endpoints, estimands, population choice etc.
QbD
[Magazine] Steven Young and Silviane de Viron's new article on Quality Tolerance Limits: An Updated View of Industry Trends gives an update on QTL adoption that, although often not included in the protocol, do give insight into critical to quality factors. Interestingly, the top 4 QTL types were on risks related to data reliability, ensuring there's sufficient data to support study endpoints, and assessing the loss to follow up. If you've got access to QTL data it may be worth taking a look and seeing what priorities study teams are focusing on downstream of protocol development.
[Webinar Recording] Martin Landray and other clinical study experts talk about the patient perspective (around the 10 minute mark) and how researchers need to lift the complexity away from the front line via good design and using relevant technology. Using personal banking as an analogy, Martin highlights the simplicity that users have when paying for coffee (i.e., contactless payment) compared to the processes that banks have to go through to record the transaction.
CIDs/Master Protocols
[Article - Methodology] Broglio et al published A Systematic Review of Adaptive Seamless Clinical Trials for Late-Phase Oncology Development that provides an overview on how adaptive designs are being deployed for oncology studies. From 68 identified studies, over half employed an efficacy gate (see figure above) to transition from phase 2 to phase 3. Interestingly, the year-on-year increase in adaptive design approaches suggest an increasing appetite towards conducting adaptive designs - possibly much in the same way that Phase 1/2 are becoming an entrenched - and therefore "standard" - approach. If you want to know more, the authors use case studies to highlight efficacy gating (INDUCE3) and arm selection (RTOG 1216) before discussing statistical, regulatory, and operational considerations.??
Protocol Tech
[Magazine] Kimberly Tableman published Digitizing Protocol Design and Deploying AI to Save Hundreds (of Hours) and Millions (of Dollars) that encapsulates the cumulative gain from transitioning protocols from paper to digital. Efficiencies in protocol development are not just in time saving but also data-informed decision making (e.g., being able to access inventories of study protocols), enabling digital data flow (e.g., protocol to EDC), and acting as a foundation for AI.
Vice President at Parexel
9 个月Thanks Jonathan, as usual, for this very informative issue!