The Future Of Clinical Trials: How AI, Big Tech, & Covid-19 Could Make Drug Development Cheaper, Faster, & More Effective

Testing new drugs is a slow and expensive process. AI has the potential to disrupt clinical trials — from patient recruitment to adherence monitoring and data collection — and Covid-19 has catalyzed its adoption

In the past year, nearly 5,000 clinical trials were launched to test life-saving treatments and vaccines for the novel coronavirus.

Covid-19 clinical trial enrollment is 80% higher than average. However, this is less impressive when considering that for many diseases, such as cancer, less than 10% of eligible patients enroll in a trial.

Patients often only enroll in a drug trial when existing forms of treatments have already failed. On top of that, not all diagnosed patients are eligible to participate — determining eligibility alone can be a herculean task.

For those that are eligible, participating in a trial is often a cost- and time-intensive endeavor. The process is inefficient for other stakeholders too: drug trials average nearly a decade, costing over $1B on average.

The $52B clinical trials market needs a makeover.

Startups and big tech are actively developing clinical trial solutions, from IoT for remote monitoring, to machine learning for electronic health record (EHR) processing, to AI-based cybersecurity for data protection.

Below, we map out a patient’s journey through a typical clinical trial process, and explore use cases for emerging technologies like AI at each step.

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