Top 20 Drug Discovery AI Startups in 2021
The search for new drugs has traditionally been a time-consuming and expensive procedure for pharmaceutical corporations. Now, with AI poised to transform the pharmaceutical industry more than any other emerging technology, a growing number of pharma and biotech companies are utilising the cutting-edge technology to reduce the hit-or-miss nature of R&D and discover new therapies at previously unheard-of speeds and accuracy.
Traditional R&D projects can take anywhere from 11 to 15 years to complete, with significant costs. Furthermore, nine out of ten medication candidates fail between phase I trials and regulatory approval, rendering the procedure inefficient and costly. To construct state-of-the-art algorithms, AI uses the most advanced biology and chemistry processes that have the ability to transform drug screening from the bench to the virtual lab without requiring a large amount of experimental data or labour.
Artificial intelligence (AI) has a wide range of applications in drug discovery, which can be divided into the following categories:
1) Target selection and validation
To forecast therapeutic potential, AI is being used to analyse the Drug Information Bank (which comprises drug candidates, gene expressions, protein-protein interactions, and clinical data records) from a public library.
2) Compound screening and lead optimization
Hits are identified, followed by Leads identification, in the compound screening and lead optimization process, where drug candidates are chosen using combinatorial chemistry, high throughput screening, and virtual screening. Virtual Screening is a compound database created by extracting large amounts of data from publically available chemogenomic libraries, which contain tens of millions of compounds annotated with structure information.
3) Preclinical studies
Preclinical studies, also known as nonclinical studies, are laboratory tests performed in vitro and in vivo to determine the efficacy and safety profile of a new therapeutic ingredient. The unsupervised approach of clustering-based AI-ML tools analyses RNA sequencing technologies for establishing molecular mechanisms of action,’ which shortens the time to acquire important large quantities of biological information.
4) Clinical trials
The creation of an AI tool for clinical trials would be perfect for recognising patient disorders, finding gene targets, forecasting the effect of molecular designs, and determining on and off-targets. AI can be utilised in Phase II and III clinical trials to detect and forecast human-relevant illness biomarkers in order to select and recruit specific patient populations, increasing the success rate of clinical studies.
A growing number of AI-enabled drug discovery startups are joining the club and a few of them that are worth keeping an eye on are mentioned below:
- Benevolent AI intends to shorten the time it takes for innovative ideas to become medications for patients by using artificial intelligence to create novel cures for some of the world’s 8,000 incurable diseases.
- Atomwise employs artificial intelligence to solve challenges that would take a human chemist many lifetimes to solve.
- Engine Biosciences has patented solutions for drug discovery and cellular reprogramming that are based on interpreting the complexity of biological networks and artificial intelligence algorithms.
- CaroCure is a rational drug research and development firm that designs and develops best-in-class medication candidates using cutting-edge technologies.
The pharmaceutical sector will be reinvented as a result of AI’s revolution in drug discovery. The advancement of AI, along with its astonishing tools, is constantly aimed at reducing obstacles faced by pharmaceutical firms, affecting the medication development process as well as the total lifespan of the product, resulting in a surge in the number of startups in this sector. Not only can AI help with quick and painless hit compound identification, but it can also help with synthesis pathway suggestions, as well as the prediction of the necessary chemical structure and a grasp of drug-target interactions and SAR. It is likely that AI will become an invaluable tool in the pharmaceutical industry in the near future.
The blog here captures the topmost promising Drug Discovery AI Startups. To read the full blog in detail, visit Top 20 Drug Discovery AI Startups in 2021
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