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Pharma companies and CROs can adjust trial design and informed recruitment tactics to enable rapid recovery and, most importantly, deliver novel medications to market faster by using crucial technology initiatives.
FREMONT, CA: The significance of Covid-19 on the life sciences industry, like many others, cannot be understated. Pharma businesses and clinical research organizations can expect further disruption as we navigate new lockdowns, from halted enrolment to delayed or abandoned trials.
Patient recruitment is still a top priority. How can those in charge of trials devise innovative techniques to speed up the process and ensure that studies stay on track? Pharma companies and CROs can adjust trial design and informed recruitment tactics to enable rapid recovery and, most importantly, deliver novel medications to market faster by using crucial technology initiatives.
The necessity to recruit patients from smaller, more diversified populations; missed deadlines and non-starter trials have occurred from a failure to recruit suitable patients, or in some cases, any patients. It is a cost the industry cannot afford at the moment. It was brought to light in particular due to trials for possible Covid-19 vaccines and the necessity to identify patients from specific population profiles. Simultaneously,
trials frequently involve vulnerable groups who are most in danger from Covid-19 exposure. As a result, a second aspect is the requirement to risk score patients as soon as possible.
Innovating Recruitment Strategies with Data
Clinical trials will be transformed by connected AI-enhanced, digital, and virtual technologies. This means prioritizing speed, safety, effectiveness, and, most importantly, patient-centricity, all of which are more important than ever as trial sponsors look for methods to save costs and boost productivity. And, by leveraging the industry's data capabilities, one can broaden the search for appropriate clinical subjects even further, breaking free from traditional methodologies.
How Covid-19 has increased the need for pre-selection and pre-screening of patients has already been noted. This is in addition to the need to make it easier for patients to enroll in clinical trials. AI and predictive analytics can also assist us in gaining deeper insights. We can weigh the patients most suitable for the research, boosting recruitment and successful retention, when we understand critical data points such as motivators, previous experiences, and even behavioral patterns. Simultaneously, AI may remove existing biases, resulting in a considerably more realistic picture.