AI (artificial intelligence) continues to expand into the biotechnology industry.

Partnerships are forming between big pharmaceutical companies and tiny biotech startups that use AI. Positive results have already come out of joint projects, notably the delay in the onset of motor neuron disease in an efficacy study conducted by SITraN on a drug candidate proposed by BenevolentBIO.

The study, led by Dr. Richard Mead and Dr. Laura Ferraiuolo at SITraN, assessed the efficacy of a drug proposed by BenevolentAI’s artificial Intelligence technology for Motor Neuron Disease (MND), also known as Amyotrophic Lateral Sclerosis (ALS). SITraN found there are significant and reproducible indications that the drug prevents the death of motor neurones in patient cell models, and delayed the onset of the disease in the gold standard model of ALS. Score one for BenevolentBIO’s AI.

The three main areas that AI is currently being used in biotechnology are: Diagnostics, Lab Assistants, Drug Discovery.

Diagnostics company Sophia Genetics takes a biopsy or blood sample from the patient, processes the sample, and then analyzes the data with their powerful analytical AI algorithms. The data analysis takes a few days with its platform, rather than several months like the current standard. The AI becomes smarter with each analysis. One day we could have an entire genome mapped and analyzed within an hour.

Lab assistants are slowing being replaced by AI. Repetitive tasks like gene editing or data analysis can be done quicker by AI programs. A company called Desktop Genetics has created an AI platform to design gene editing constructs using CRISPR. The power of AI allows them to more quickly and effectively construct CRISPR libraries.

The most exciting area of AI though is in drug discovery. It takes about $2 billion and 12 years to advance a single drug through clinical trials and then to your kitchen cabinet. AI can make drug discovery cheaper and much faster. Small AI companies and big pharmaceutical companies are increasingly forming partnerships. Some AI companies are offering drug discovery from a genetics perspective where genomes are analyzed. Other AI companies offer rapid computer vision to analyze images of cells after being exposed to a certain drug compound. This AI method is much faster than a human looking into a microscope or on a screen for drug compounds of interest.

A company called Biorelate employs AI to analyze and dig out relevant information from scientific literature. Imagine wanting to know what scientific literature there is on a certain drug compound? Instead of searching literature databases, the AI can search the literature for scientists and pull out the relevant information.

A company called e-Therapeutics is reducing the time and money it costs to develop new drugs with the help of an AI platform that can explore large amounts of public and private databases to model complex diseases and select the most promising compounds to treat them.

LifeArc and the Milner Therapeutics Institute have partnered up to use AI to find and test drug targets for cancer and respiratory diseases. The AI will predict the efficacy of new and existing drugs in specific patient populations.

Swiss company Sophia Genetics has made an AI for leukemia. The AI test called Myeloid Solution allows the detection of mutations that cause blood cancers like leukemia. The AI can read genome regions rich in GC base pairs, which can cause problems for human researchers. This means that key biomarkers of blood cancers like mutations to the CEBPA, FLT3, and CALR genes can now be detected. The AI data analysis technology is combined with liquid biopsies, which could become the holy grail of early cancer detection. Another AI company called ANGLE recently claimed that the use of its AI could save healthcare providers $5,000 per prostate cancer patient.

Sophia Genetics did this AI promo video on YouTube that will give you a better idea of how they are using AI in biotechnology:

Where Things Are Headed For Stock Traders

Unless a big biotech company goes with a generic solution like IBM’s Watson, what is to stop these small AI startups from conducting their own clinical trials and ultimately selling the drugs they find themselves?

In order to protect marketshare, we could see big biotech companies buying AI startups and then using the technology in their own R&D structures. If big biotech companies don’t move quickly to acquire these startup AI companies, market leaders could slowly begin to falter and fall behind in drug development.

Biotech AI In the News