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The Friction Factor: Solving Delays in Clinical Trial Efficiency
Friction exists in every multi-stakeholder endeavor. Imagine the stakeholders in clinical trial design and implementation as a chain that links together participants lived experiences and biological responses into data that demonstrates outcomes. Multiple stakeholders from Pharmaceutical companies to patient panels, clinical research organizations (CROs) to technology vendors, interact as “links” to innovate better health outcomes for patients through better research outcomes.
What Biology Can Teach Us about Patient-Centric Research
The push to make clinical trials more patient-centric from regulatory bodies and innovative organizations has led to many claims: "Listen to patients," "leverage decentralization," "engage more ethnically diverse Principal Investigators to access ethnically diverse participants." Each of these claims have merit, yet for all the patient panels convened, patient-centric consultants hired, and internal initiatives launched, data has yet to fully realize meaningful shifts in the accessibility of clinical trials to most folks. I’d like to suggest that is because even the most valuable initiatives, while necessary, are rarely sufficient to create patient-centric clinical trials.
3 Ways to Improve Clinical Trial Efficiency
Clinical trials introduce innovation in medicine. However, they can be very inefficient. There are multiple factors that slow progress and increase costs. Here are three ways to improve the efficiency of a clinical trial.
Increasing Diverse Clinical Populations: Race & Ethnicity
The lack of representation and diversity in medical research is partially driven by a lack of access to clinical trials. Studies with limited diversity can create significant limitations on the conclusions drawn from study data. Attracting a diverse population of patients for a clinical trial is critical for patient health and long-term community wellness.
Increasing Diverse Clinical Populations: Sex
In Part I, we’ll look at how research can better address often overlooked gender based differences as an underappreciated variable in the evidence generated in the clinical development lifecycle and why extrapolation of results from one gender to another is objectionable.