Top Companies Using A.I. In Drug Discovery And Development

What if coming up with a new drug could be measured in days rather than years? What if new medication would cost thousands instead of billions of dollars? Just look at how an A.I. pharma start-up recently developed a potential new drug in 46 days! Artificial intelligence technologies promise to speed up the process of drug discovery and development and make it more cost-effective. As the market is flourishing, and it takes time and effort to separate the wheat from the chaff, we collected the most promising A.I. pharma companies out there.

The future is about speed and savings

New drugs are approved through human clinical trials: rigorous, year-long procedures starting in animal trials and gradually moving to patients. They typically cost billions of dollars and take many years to complete, sometimes more than a decade. Plus, patients in trials are exposed to side effects that cannot be predicted or expected. And even if the trial is successful, it has to go through a regulatory approval: it may or may not receive the nod of the respective regulatory agency, e.g. the US Food and Drugs Administration (FDA).

Luckily, there’s an abundance of technologies and companies who want to change the status quo. One way to modernize the drug testing process is applying technologies to the traditional framework, for example, through online platforms to seek out participants; while an alternative way is to use human organs-on-chips or in silico trials. These all aim to speed up the process, save thousands of dollars and unburden patients. 

However, when looking at all these technologies, artificial intelligence is the most advanced and most multifaceted. The technology helps companies aggregate and synthesize a lot of information that’s needed for clinical trials, thus shortening the drug development process. It can also help understand the mechanisms of the disease, establish biomarkers, generate data, models, or novel drug candidates, design or redesign drugs, run preclinical experiments, design and run clinical trials, and even analyze the real-world experience. The number of already existing A.I. companies in drug development reflect the manifold usage of the technology: they are many and increasing day by day. Nevertheless, we managed to choose our seven favorites, so here you go!

Source: Wired

1) The company that mines clinical trials: Antidote

US and UK-based Antidote is focusing on matching patients and medical researchers in clinical trials so they could work together more easily. The platform allows patients to find the most suitable clinical trials, helps researchers stream their latest study information to millions of patients, and even connects them with members of the medical community directly. It’s basically a very efficient online platform for enhancing access to clinical trials.

By combining proprietary technologies, data, and well-established business models, the company is transforming the way patients and researchers connect so that breakthroughs happen faster. The company was launched with the name of TrialReach in 2010, but it got rebranded to Antidote in 2016.

Source: www.wired.com

2) The company with tangible results: Atomwise

The most well-known company in drug discovery aims to reduce the costs of medicine development by using supercomputers to predict from a database of molecular structures, in advance, which potential medicines will work, and which won’t. Their deep convolutional neural network, AtomNet, screens more than 100 million compounds each day.

In 2015, Atomwise launched a virtual search for safe, existing medicines that could be redesigned to treat the Ebola virus. They found two drug candidates predicted by the company’s AI technology which may significantly reduce Ebola infectivity. This analysis, which typically would have taken months or years, was completed in less than one day! Imagine how efficient drug creation would become, if such clinical trials could be run at the “ground zero” level of health care, namely in pharmacies.

Source: www.techcrunch.com

3) The company that concentrates on cancer drugs: Turbine.AI

A dedicated team of A.I. developers, medical professionals, and bioinformaticians has spent 6 years researching and building an artificial intelligence solution to design personalized treatments for any cancer type or patient faster than any traditional healthcare service. The technology models cell biology on the molecular level; it can identify the best drug to target a specific tumor with, moreover it identifies complex biomarkers and design combination therapies by performing millions of simulated experiments each day.

The key to Turbine’s uniqueness is its molecular model of cancer biology guided by an A.I. to identify the biomarkers that signal sensitivity to treatment. As a result, the technology is already used in collaborations with Bayer, the University of Cambridge and top Hungarian research groups to find new cancer cures, speed up the time to market, and save the lives of patients suffering from currently incurable forms of the lethal disease.

4) The company that brings in the genomic component: Cambridge Cancer Genomics

The company, founded in 2016 and based in Cambridge, UK, develops precision oncology solutions to transform the way cancer patients are treated. They believe that the more clinical and genomic data oncologists have, the smarter decisions they can make about drug usage in any given circumstance – and thus, they use machine learning and data analytics to give doctors this power.

Using simple blood draws, CCG shortens the time required to know whether treatment is working, thus allowing changes in the used therapy and reducing unnecessary side effects. CCG can also identify relapse an average of seven months earlier than standard practice.

Source: www.techcrunch.com

5) The company with a comprehensive structure from genomic to clinical data: Row Analytics

The Oxford-based data analytics company operating since 2013 specializes in digital health, precision medicine, genomics, and semantic search. It is delivering a range of highly innovative data analytics platforms, for example, precisionlife for drug discovery.

The platform combines A.I. methods and data analytics to look at multiple genetic variants in combinations across a range of diseases. As they are able to complete the process in weeks instead of months, even for large disease populations with tens of thousands of patients, this enables the rapid identification of novel drug candidates and potential drugs to repurpose.

Source: www.the-scientist.com

6) The company with research excellence of in silico genomics: Deep Genomics

Brendan Frey’s company promises to solve the biggest puzzle in genetics: to get to know exactly what information the genome could provide for patients, medical professionals, and researchers. For doing so, Deep Genomics is leveraging AI, specifically deep learning to help decode the meaning of the genome.

So far, the company has used its computational system to develop a database that provides predictions for more than 300 million genetic variations that could affect the genetic code. For this reason, their findings are used for genome-based therapeutic development, molecular diagnostics, targeting biomarker discovery and assessing risks for genetic disorders.

Source: www.liquid-logic.com

7) The company with drug discovery in 46 days: Insilico Medicine

As an artificial intelligence company for drug discovery, biomarker development, and aging research, Insilico Medicine aims to cover the entire process of drug discovery, clinical trials analysis, and digital medicine. It is pursuing internal drug discovery programs in cancer, dermatological diseases, fibrosis, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging.

The company, working with researchers at the University of Toronto, made headlines lately with the announcement that the process of developing a new drug candidate last just 46 days with the help of its smart algorithm. At first, it took 21 days for the team to create 30,000 designs for molecules that target a protein linked with fibrosis (tissue scarring). They synthesized six of these molecules in the lab and then tested two in cells; the most promising one was tested in mice. The researchers concluded it was potent against the protein and showed “drug-like” qualities. The research was published in Nature Biotechnology.

Dr. Bertalan Mesko, PhD is The Medical Futurist and Director of The Medical Futurist Institute analyzing how science fiction technologies can become reality in medicine and healthcare. As a geek physician with a PhD in genomics, he is a keynote speaker and an Amazon Top 100 author.

Subscribe here for The Medical Futurist newsletter to get exclusive details about digital health!