Simply, Artificial intelligence (AI) means machine learning and behaving like humans which ultimately facilitates works of humans.
Whether you do aware or not but in the modern world, we are all surrounded by AI. There are many examples of AI which we are using (may be unknowingly) in our day to day life. For exm, social media, search engines, product recommendations, Email filters etc.
This is forth industrial revolution where AIs have taken over the world. And Pharmaceutical and healthcare sector are most affected industries by AI. Today, we shall see top 10 (2019) highest grossing pharmaceutical companies which are using AI or machine learning for drug discovery, clinical research, disease diagnosis, novel medication, predictions, data analysis etc.
Pfizer promoted a drug discovery partnership with IBM Watson. In December 2016, Pfizer and IBM announced a partnership to accelerate drug discovery in immuno-oncology.
In May 2018, Pfizer had fastened AI collaboration. Massachusetts Institute of Technology announced Pfizer as a member of its Machine Learning for Pharmaceutical Discovery and Synthesis Consortium. Pfizer also announced a partnership with Chinese tech startup XtalPi for molecular stability of an organic compound and advanced their work in drug designing. As reported by the wall street journal, Pfizer built analytics platform to identify patients with rare diseases that might previously have gone undiagnosed.
In September 2018, Pfizer announced to evaluate Atomwise’s platform to identify potential drug candidates for up to three target proteins selected by Pfizer.
CytoReason, a leader in machine learning for drug discovery and development, announced that it had entered into a collaboration agreement with Pfizer Inc. that will leverage CytoReason’s cell-centered models of the immune system. CytoReason’s proprietary platform helps rebuild lost cellular information from gene expression data and associates genes to specific cells. This information is then integrated with additional omics and literature data to create a cell-based model of the trial-specific immune response.
In April 2019, Pfizer joined with Concerto HealthAI to use AI and real world data in oncology. The collaboration will conduct novel synthetic control arm and prospective Real World Data outcomes study designs for therapeutics that are both pre- and post-approval.
In September 2019, Pharmaceutical giant Pfizer announced plans to launch a one-year pilot program with robotics company Catalia Health, maker of Mabu, a home robot that coaches patients on health and prescription drugs. The main idea behind this collaboration is to understand patients clinical journeys using artificial intelligence.
Roche has developed a machine learning diagnostic techniques for diabetic macular edema, a complication of diabetes that causes a thickening of the retina and lead to blindness. Roche can utilise its vast clinical trial database to develop AI algorithms to predict the presence of disease, risk of disease progression, and response to treatment; all of which could be supplied to ophthalmologists to deliver higher quality personalised healthcare.
In February 2018, Roche acquired Flatiron Health, an oncology-focused electronic health records company. Flatiron's massive amount of oncology data provides Roche with a tremendous asset for machine learning.
Roche is working with medical research machine learning startups like Owkin and Exscientia.
After becoming CEO of Novartis, Vasant Narasimhan took revolutionary steps towards implementation of Artificial intelligence in Novartis which proven to be global footprints for others.
Novartis was able to decode cancer pathology images through AI. Novartis joined with Tech startup PathAI and created a system through which they are able to diagnose cancer.
In June 2017, Novartis joined with IBM Watson for breast cancer clinical trial in which IBM was contributed its data analytics and machine learning chops to better understand the expected outcomes of various breast cancer treatments.
In January 2018, Novartis partnered with McKinsey’s QuantumBlack to analyze 500 clinical trials operations with machine learning around the world in realtime.
In May 2018, MIT announced that Novartis became a member of its Machine Learning for Pharmaceutical Discovery and Synthesis Consortium. In the same month, Intel collaborates with Novartis on the use of deep neural networks to accelerate high content screening, a key element of early drug discovery.
Novartis also collaborate with the University of Oxford’s Big Data Institute (BDI) to identify early predictors of patient responses to treatments for inflammatory diseases, such as multiple sclerosis (MS) and psoriasis. They also worked to identify patterns in data, often across multiple data sources and types (imaging, genomics, clinical and biological), which cannot be detected by humans alone.
In June 2019, the MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery) consortium created by 17 partners across Europe and Novartis was one of its members. Through this platform companies will develop more accurate models to predict which compounds could be promising in the later stages of drug discovery and development.
On September 2019, Novartis and Microsoft announced a multiyear alliance which will leverage data & Artificial Intelligence (AI) to transform how medicines are discovered, developed and commercialized. Novartis is also establishing an AI Innovation Lab to empower associates to use AI across their business. Joint research activities will include co-working environments on Novartis Campus (Switzerland), at Novartis Global Service Center in Dublin, and at Microsoft Research Lab (UK) – starting with tackling personalized therapies for macular degeneration; cell & gene therapy; and drug design.
4. Johnson & Johnson
Johnson & Johnson announced results of a new real-world study, which found newly diagnosed patients with nonvalvular atrial fibrillation (NVAF) taking XARELTO® (rivaroxaban) experienced significantly fewer strokes, significantly fewer severe strokes and fewer stroke-related deaths compared to those taking warfarin using artificial intelligence. The study also found that XARELTO® significantly reduced overall strokes (across all severities) by 18 percent compared to warfarin and reduced the risk of experiencing the most severe strokes.
Janssen has developed Neutrogena Skin360™ app which uses artificial intelligence (AI), to track your skin's progress over time to give you deep information about your skin's actual needs and health. It lead to personalize skincare.
Johnson & Johnson Vision introduced Andy, a virtual assistant chatbot powered by artificial intelligence (AI). It helps U.S. consumers throughout their ACUVUE® Brand Contact Lens journey – from those considering contact lenses for the first time to long-term wearers. The chatbot also provides intuitive coaching to help new wearers develop healthy contact lens habits.
J&J acquired Auris Health which develops robotic technologies and its first product, the monarch platform has been approved by the USFDA which allows surgeons to reach small and hard-to-access lung nodules early to diagnose and treat lung cancer.
In November 2016, J&J joined with BenevolentAI and allowed it to select number of novel clinical stage drug candidates and their extensive related portfolio of patents. Under the terms of the license agreement, BenevolentAI will have the sole right to develop, manufacture and commercialise these novel drug candidates in all indications and in all territories.
In January 2018, Johnson & Johnson joined with WinterLight Labs to try predicting dementia and neurodegenerative diseases from voice samples obtained through Janssen clinical trials.
Janssen is a founding member of Alliance for AI in healthcare (AAIH). AAIH works for advancement and use of artificial intelligence in healthcare to improve patients’ lives and create more efficient, sustainable, and accessible healthcare systems.
In April 2019, Janssen collaborate with AI-driven drug design startup Iktos to use Iktos' virtual drug design technology on small molecule drug discovery projects.
In June 2019, the MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery) project announced Janssen as one of its members.
5. MSD (Merck & Co., Inc., Kenilworth, N.J., USA)
Merck and Wayra UK are working together (part of Spanish telecoms business Telefonica) under the banner of the ‘Velocity Health’ programme. The Velocity Health programmes focused on prevention in healthcare with an emphasis on diabetes prevention and cancer prevention.
FDA grants breakthrough device designation to artificial intelligence software for Chronic Thromboembolic Pulmonary Hypertension pattern recognition from MSD and Bayer. The software processes image findings of cardiovascular, lung perfusion and pulmonary vessel analyses in combination with the patient’s history of pulmonary embolism.
Merck (MSD) and Accenture in collaboration with Amazon Web Services (AWS), launched a cloud-based informatics research platform to improve productivity, efficiency and innovation in the early stages of drug development.
Merck Sharp & Dohme (MSD) Corp., a subsidiary of Merck & Co., Inc has developed an Artificial Intelligence (AI) chat bot. The MSD Salute chat bot is designed to aid physicians in providing product information and pathology.
Sanofi Genzyme, the specialty care global business unit of Sanofi joined with Recursion Pharmaceuticals to deploy its drug repurposing platform to identify new uses for Sanofi’s clinical stage molecules across dozens of genetic diseases.
Sanofi joined with Exscientia (AI driven company) to identify and validate combinations of drug targets for metabolic disorders like diabetes. In August 2019, Exscientia announced that Sanofi exercised its option for a bispecific small molecule targeting inflammation and the progression of fibrosis.
Sanofi joined with BERG to use BERG's proprietary Interrogative Biology® platform to assess potential biomarkers of seasonal influenza vaccination outcomes in an unbiased and data-driven manner.
Sanofi also connected with Researchably, a young startup incubated at UC Berkeley, for conducting a pilot with Sanofi in China, using AI to sift through thousands of research studies and surface the most relevant ones to pharma stakeholders.
In June 2019, Sanofi joined with Google to establish a new virtual Innovation Lab. Through this partnership, they will leverage deep analytics across data sets to better understand key diseases and extract related patient insights. They were also planned to apply artificial intelligence (AI) across diverse datasets to better forecast sales and supply chain efforts.
Abbvie is working with AI very silently. But it does have a confidential project listed with Atomwise.
In September 2016, AbbVie partnered with AiCure to use AI-based patient monitoring platform improved adherence in an AbbVie phase 2 schizophrenia trial.
8. GlaxoSmithKline (GSK)
GSK is very active to utilize artificial intelligence for drug disvocery and they have created an in-house artificial intelligence unit. Initially it was called "Medicines Discovered Using Artificial Intelligence.” And then renamed as “In silico Drug Discovery Unit.” As of July 2019, GSK's AI team reportedly numbered about 50.
GSK joined with Google to create biomedical medicines which are implantable devices that can modify electrical signals that pass along nerves in the body, including irregular or altered impulses that occur in many illnesses.
GSK has partnered with startups including Exscientia and Insilico Medicine. 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. The partnership with Insilico, announced in August 2017, is to identify novel biological targets and pathways.
GSK is a founding member of Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium whose goal is to transform drug discovery from a slow, sequential, and high-failure process into a rapid, integrated, and patient-centric model. GSK provided more than 2 million compounds from its historic and current screening collection, as well as preclinical and clinical information on 500 molecules that have failed in development. GSK is also a founding member of Alliance for AI in healthcare (AAIH). AAIH works for advancement and use of artificial intelligence in healthcare to improve patients’ lives and create more efficient, sustainable, and accessible healthcare systems.
GSK is also a member of MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery) project which will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.
Cloud Pharmaceuticals, Inc., an Artificial Intelligence-driven drug design and development company, announced that they have entered into drug discovery collaboration with GSK. Cloud will design novel small-molecule agents to GSK specified targets.
GSK joined along with Exscientia and they created a highly potent in vivo active lead molecule, targeting a novel pathway for the treatment of chronic obstructive pulmonary disease (COPD).
GSK also has a collaboration with researchers at the Universities of Strathclyde and Nottingham that focuses on applying AI to synthetic chemistry.
Amgen is an investor in precision medicine startup GNS Healthcare.
In May 2018, MIT announced that Amgen was a member of its Machine Learning for Pharmaceutical Discovery and Synthesis Consortium. Amgen is also working with medical research machine learning startup Owkin.
Amgen is also a member of MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery) project which will train machine learning models on datasets from multiple partners while ensuring the privacy of each partner using federated learning.
10. Gilead Sciences
Gilead's first publicly announced use of AI in drug discovery was in April 2019. This month, Gilead announced a strategic collaboration with stealthy startup Insitro. The collaboration will focus on nonalcoholic steatohepatitis (NASH). Gilead will use Insitro's platform to create disease models for NASH and find targets that affect the disease's progression and regression.
And not only these but many other top pharmaceutical industries are using AI for their day to day problems. This is the new area where pharmacists should concentrate and get lucrative opportunities.