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33 Pharma Companies Using Artificial Intelligence in Drug Discovery

If you read my list of startups using artificial intelligence to drug discovery, you may have wondered: how much traction do these companies actually have?

To help answer such questions, this post summarizes how pharmaceutical companies apply artificial intelligence in drug discovery, including through partnerships with AI startups.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

ProteinQure is a fellow Canadian AI drug discovery company that uses quantum computing, molecular simulations, and machine learning to design drugs.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

A Numerate press release states that it is 'leveraging the power of cloud computing and novel computational methods to transform the drug design process.'

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

But there are startups out there that focusjust on doing this, like Winterlight Labs.) In February 2018,Bristol-Myers Squibb (BMS) announced entering into a partnership with Sirenas to apply the biotech company's technology to challenging therapeutic targets.

In March 2019,BMS announced another partnership, with Concerto HealthAI.Concerto specializes in using AI to analyze real-world oncology data in order to generate insights and real-world evidence.

Its partnership with BMS covers a range of data sources, cancers, and activities, including clinical trials, protocol design, and precision oncology treatments.

In June 2017, Genentech and precision medicine startupGNS Healthcare announced a partnership to find and validate potential cancer drug targets by analyzing data from sources such as electronic medical records and next generation sequencing.

The partnership with Excscientia, announced in July 2017, is to discover novel and selective small molecules for up to 10 disease-related targets across undisclosed therapeutic areas.

(For more information on how GSK became such a leader, check out my article “6 Steps to AI Leadership in Pharma: An Interview with John Baldoni of GSK.”) In May 2018, GSK announced a partnership to use AI for the design of novel small-molecule drugs with Cloud Pharmaceuticals.

In early April 2019, Exscientia announced that its partnership with GSK had produced its first tangible result:a 'highly potent'lead molecule targeting a novel pathway for chronic obstructive pulmonary disease.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

In November 2016, they announced that BenevolentAI would license the right to develop, manufacture, and commercialize clinical stage drug candidates from Janssen after using artificial intelligence to identify untapped potential in Janssen's portfolio.

This deal may already be bearing fruit, as BenevolentAI recently launched a phase 2b trial for a drug from the partnership to treat sleepiness in people with Parkinson's disease.

(In fact, Janssen issued a press release that was one of the few sources that mentioned all the initial members.) MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

In July 2019, Celsius Therapeutics announced a partnership with Janssen to use its single-cell genomics and machine learning platform to find predictive biomarkers of response in Janssen’s VEGA study of golimumab (Simponi) and guselkumab (Tremfya) in patients with ulcerative colitis.

In December 2018, Merck announced a partnership with Cyclica to use its AI-augmented proteome screening platform toelucidate mechanisms of action, evaluate safety profiles, and explore additional applications for investigational small molecules.

few months later, in March 2019, Merck announced a partnership with Iktos to useits generative AI to design novel molecules with desired properties for a specified disease.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

March 2018 report also describes a partnership with IBM Watson to improve clinical trial recruitment, and the use of a “digital cortex” to predict medication efficacy.

In June 2018,Business Insider published an interview with the outspokenJay Bradner, president of the Novartis Institutes for BioMedical Research (NIBR), about the company's progress with artificial intelligence.Bradner stated that 4% of the 6,000 scientists working at NIBR are data scientists.'We like to think of ourselves as the lead turtle in the race of the turtles,' he said, referring to pharma's conservative adoption of emerging technology.

In January 2019, the company announced a partnership with the University of Oxford’s Big Data Instituteto predict how patients respondto drugs.The work willcombine different types of data, such as clinical, imaging, and genomics data.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

few months later, in December 2018, Novo announceda deal with UK biotech e-Therapeutics to use its AI-based drug discovery technology to find newtreatments for type 2 diabetes.

There has been little announced since (at least, that I can find), but a string of negative reports about IBM Watson's capabilities (here, here, here, here, here, here, and I could go on), including in healthcare, call into question how fruitful the partnership might have been.

In previous work, the startup has discovered new cellular players in melanoma, new mechanisms of action in atopic dermatitis, and novel pretreatment biomarkers in inflammatory bowel disease anti-TNFα therapy.CytoReason will standardize and organize Pfizer's data and integrate it into aPfizer-specific immune system model.

In April 2019, Concerto HealthAI announced a partnership with Pfizer to use AI and real world data in oncology.The partnership aims tofindactionable insights for Pfizer's investigational and commercialized therapiesfor solid tumors and hematologic malignancies.

Their partnership, announced in May 2017, focuses on finding bispecific small molecule drugs for metabolic diseases such as diabetes and their comorbidities.

Through a new virtual 'Innovation Lab,' Sanofi and Google will analyze real world data to understand what treatments work for patients, and analyze manufacturing and commercial data to forecast sales and inform marketing and supply chain activities.

Another partner of the very active Numerate, Servier and the startup announced in June 2017 a collaboration to design small molecule modulators of ryanodine receptor 2 (RyR2), a target thought to be important in cardiovascular disease that has eluded drug-ability.

MELLODDY will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.

In April 2019, SK Biopharmaceuticals, a Korean company that focuses on disorders of the central nervous system and cancer, announced an agreement with twoXAR to develop new treatments for non-small cell lung cancer.

Let me know in the comments.) One of Exscientia's early partners, Sumitomo Dainippon and the startup announced in September 2015 initial results of a collaboration to identify new treatments for psychiatric diseases.

Another Numerate partner, Takeda and the startup announced in June 2017 that they would collaborate on identifying candidates for oncology, gastroenterology, and central nervous system disorders.

In January 2019, Takeda partner Recursion announced an expanded partnership with the pharmaceutical company to evaluate and identify novel preclinical candidates for rare diseases.

Jeremy Howard: fast.ai Deep Learning Courses and Research

He is also a Distinguished Research Scientist at the University of San Francisco, a former president of Kaggle as well a top-ranking competitor there, and in general, he’s a successful entrepreneur, educator, research, and an inspiring personality in the AI community.

This conversation is part of the Artificial Intelligence podcast.If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations.

Are psychiatrists really ready for the AI revolution?

The World Health Organization estimates that up to 15% of the population experiences mental health disorders.

Smartphones and wearable sensors offer people the ability to monitor themselves and to benefit from the way deep learning can analyze the data.

Indeed, these techniques are already being used to detect the changes in mood that indicate bipolar disorder or to detect people at risk of depression.

“To our knowledge, this is the first global survey to seek the opinions of physicians on the impact of autonomous artificial intelligence/machine learning on the future of psychiatry,” say the team.

The researchers randomly chose a sample of 750 professional psychiatrists registered with an online database of over 800,000 health-care professionals around the world, including 22 countries in North and South America, Europe, and Asia;

“An overwhelming majority (83 per cent) of respondents felt it unlikely that future technology would ever be able to provide empathic care as well as or better than the average psychiatrist,” say Doraiswamy and colleagues.

And yet only half the psychiatrists felt that artificial intelligence would substantially change their jobs (presumably the same half who think AI can better diagnose conditions than humans).

The report pointed out that apps focused on mental health are among the fastest-growing sectors in the global digital health market.These kinds of apps could make a big difference.

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