Google Research and Google DeepMind recently released a paper announcing the creation of a new LLM for drug discovery and therapeutic development dubbed Tx-LLM, fine-tuned from PaLM-2. Tx-LLM utilizes ...

As sponsors advanced more niche and personalized modalities, manufacturers were pushed to adopt holistic approaches to safety ...

Overview Artificial intelligence seems to be transforming drug discovery in 2026, enabling faster molecule design, smarter ...

Many biological functions are regulated by the switching on and off of mechanisms triggered by the matching of a keyhole ...

The role of natural products in drug discovery in India was discussed at the inaugural session of the National Conference on Translational Opportunities in Natural Products Research, organised by the ...

Single 2.6B-parameter model achieves state-of-the-art performance across drug discovery benchmarks while running entirely on private pharmaceutical infrastructure ...

How innovative technologies like AI and gene editing are advancing rare disease drug discovery and development.

Written by Keynote Contributor Soroosh Afyouni, head of health data science at bioXcelerate AI. Every household seems to have that drawer of miscellaneous belongings. When you need something, you know ...

Despite significant progress in medicinal chemistry and life sciences research, drug discovery and development remain slow and expensive, taking on average approximately 15 years and US$2 billion to ...

Merck & Co. Inc. MRK on Wednesday announced a strategic collaboration with Mayo Clinic to leverage artificial intelligence (AI) and advanced analytics in drug discovery. This partnership aims to ...

Developing high-quality, safe, and effective drugs is a complex process that requires varied scientific skills and stringent regulatory assessments. Drug development is a process that spans many years ...

Traditionally, developing a new drug takes many years and requires a massive financial investment, often involving significant risk and a high likelihood of failure. AI models trained on extensive ...