Can We Move Fast Without Breaking Trust?

The average timeline for developing a new drug runs up to 10-15 years, while 90 per cent of pharmaceutical industry endeavours fail in clinical trials and even more in pre-clinical research. Can AI help us expedite the drug discovery process safely and effectively?

- BY PAROMITA GUPTA

298 days. It took India 298 days to approve the restricted use of Covaxin, its first indigenous COVID-19 vaccine by Bharat Biotech and the Indian Council of Medical Research (ICMR), and Covishield, an Oxford-AstraZeneca vaccine manufactured by the Serum Institute of India. During this period (March 11 to January 3, 2021), the pandemic death toll in the county had reached 1.5 lakh.

The average timeline for developing a new drug runs up to 10-15 years. However, Covaxin boasted of a timeline of 120 days for manufacturing, testing, and releasing a batch, while Covishield's development and deployment took about eight months. These record paces, coupled with Covaxin's then-incomplete Phase 3 trials, were met with widespread criticism from the scientific leaders and minds.

“What if we roll out a vaccine with unknown efficacy and later find it to be only 50 per cent efficacious? Would it be fair to people who received it?” said Dr Shahid Jameel, a leading virologist, in the media back then. With anticipated public hesitancy and criticism, India went ahead with the two vaccines to combat the healthcare crisis, emerging victorious with positive results. In November 2021, Covaxin was found to be “highly efficacious (producing the desired result of 78 per cent)” and gained approval from the World Health Organisation (WHO).

While this was a once-in-a-lifetime crisis, such a process cannot be easily replicated or guaranteed to yield constructive results. This is where artificial intelligence (AI) can play a pivotal role in expediting the bench-to-bedside translation of pharmaceutical (pharma) innovations.

AI IN PHARMACEUTICAL INDUSTRY