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Co-Creating Research with Patients
On this episode of Healthcare Uncomplicated with Joao Bocas, he talks about ‘Co-creating research with Patients’ with John Reites, CEO of THREAD. In the short video, they discuss how the industry is bringing patients into the study process earlier and some of considerations to take when co-creating a clinical trial.
3 Considerations for Creating a Patient-First eCOA Solution
Researchers are working hard to create more accessible activities (think inputs) for patients so they can get in and get out quickly - but what if we did both? Unfortunately, it's not as simple as it sounds but the reality is any truly functional eCOA strategy will require a creative approach to both inputs and processes. Here are three ways you can get started on your journey of putting the patient first in your eCOA.
How Voice Response Technology Can Aid Clinical Trials
Why the gap between spending and impact? Patient awareness, inconvenience, and rationale remain limited, debilitating, and confusing. It seems pharma companies often design clinical trials without first talking to patients and determining their needs and expectations.
The Benefits of Using eCOA in Clinical Trials
eCOAs are not new, but despite being recommended by regulatory authorities like the U.S FDA, many study teams still choose to collect assessment data with pen and paper. Find out why paper COAs add unnecessary risk, especially with trials becoming more advanced and the industry acknowledging the need to reach more diverse and widely dispersed populations of patients.
Realizing The Potential Of AI And Machine Learning In Clinical Research
Over the last few years, talking about artificial intelligence (AI) and machine learning (ML) could drive customer interest, make something sound more innovative or even appear to boost a company’s valuation. Unfortunately, many of these AI/ML talking points were general, potentially premature and not yet ready to offer results. The clinical research industry was not immune to these discussions and may largely still view many AI and ML approaches as something on the horizon rather than as something available today.