Here comes an AI-based process to shorten drug discovery cycle

K V Kurmanath Updated - October 19, 2023 at 09:47 PM.

Chip design firm says it has come up with a new development methodology that can save costs   

The company, which taped-out a 5-nanometer chip in 2022, would use a 16-nm chip to work on the drug discovery. 

Drug discovery is a painstaking process. The majority of attempts often go waste after 6-8 years of working on a drug, making it an inordinately expensive exercise. A chip design company, a US-based firm with an R&D centre in Hyderabad, claims that it has found an AI-backed method to cut the process short and save costs.

Venkat Mattela, Founder and Chief Executive Officer of Ceremorphic, said that the company has created a computer-generated cell, which mimics a human cell, making it easy for researchers to understand how it reacts when exposed to a disease or a drug.

Mattela sold his earlier venture Redpine Signals to Silicon Labs for $308 million in 2020

“The aim is to shorten the development cycle and reduce the side effects by choosing the right molecule based on new development methodology,” he told businessline here on Thursday.

“Over 90 per cent of drug candidates fail at the clinical phase-ii stage and the number of new drugs cleared by FDA every year is small. This calls for a new development methodology in the early stages of the design pipeline,” he said.

The firm has started an exclusive Life Sciences division with about 32 people to work on oncology and neurology, with over 70 per cent of them working out of its Hyderabad R&D facility. The team comprised computational biologists, chemists, computer scientists and analog hardware designers.

The company, which taped-out a 5-nanometer chip in 2022, would use a 16-nm chip to work on the drug discovery.

“Accurate AI foundation models, new algorithms and data are critical to producing successful later stage results,” he said.

“Deploying our proprietary analog circuit technology, supercomputing chips and novel AI algorithms, we developed an architecture that can predict the later stage outcomes to increase R&D efficiency,” he said.

He claimed that this innovation would transform the future of drug discovery to accelerate making personalised medicine a reality.

For the subsequent levels in drug discovery, the company plans to forge alliances with relevant life sciences companies.

Published on October 19, 2023 16:17

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