World Clinical Trials Day, May 20, marks the date of the first randomised clinical trial, held aboard a ship in 1747. Today, as part of biopharmacetuical R&D, clinical trials is the area where the spend is the highest and provides the most opportunity for automation and adoption of artificial intelligence (AI). Sowmyanarayan Srinivasan, Managing Director – Life Sciences, Accenture Advanced Technology Centers in India (ATCI) predicts that the future of clinical trials will be fully AI-enabled, starting right from protocol to clinical operations around site and investigator management and eventually pivoting to patients and making it easier for the patients to be part of clinical trials
The global biopharma industry is undergoing significant transformation across the spectrum of drugs, drug delivery and business model. There is an increasing focus on patient at the core. Some of the key drivers of the transformation are –
- End of blockbuster era and beginning of niche buster era. The drugs are getting more personalised and relevant for much smaller populations. This also means that the number of drug launches are increasing
- Focus on new science driving more companion and digital solutions as approved drugs, genomics is driving personalised drugs
- Healthcare consumerisation is being driven by the digital revolution. Patients do not want to be held back by disease and want to be treated more like consumers. They are looking for same experiences as in their daily lives, for example retail
- In North America and Europe, the focus on outcomes has increased and reimbursements are tied to defined and agreed outcomes
According to a recent report (1), while the transformation is driving a change in pricing models and patient engagement, the costs of bringing a drug to the market continues to increase and is projected to be worth $2 billion. This situation has created a perfect storm to reimagine the entire biopharma R&D process which is the main cost contributor in getting the drug to the market.
As biopharma organisations focus on reimagining the R&D process, one of the key enablers of this change is Artificial Intelligence (AI). Though AI has existed for several years (in fact decades), the adoption in the biopharma industry was slow and has increased significantly in the last six to eight years. This adoption can be directly attributed to increased generation and availability of data, ‘big data.’ There has been a tremendous increase in both volume and variety of data – genomics data becoming mainstream and cost effective, imaging data and the ability to store and analyse such data, patient data from digital solutions and patient medical data with higher adoption of EMR and EHR. In this evolution, the bottleneck moved from quantity of data to quality of data and curation, though the fact that data is available for leveraging artificial intelligence techniques is a critical factor for increase in adoption.
If you look at the history (2) of clinical trials, the first clinical trial of a novel therapy was accidentally conducted in 1537 and it took over 200 years (year 1747) to the first controlled clinical trials and another 200 years (year 1946) to the first double-blinded-controlled trials, which has been the norm since that time.