Improving healthcare IT infrastructure to drive the growth of global AI in drug discovery market
According to TechSci Research report, “Global AI in Drug Discovery Market By Component (Software v/s Services), By Technology (Machine Learning, Deep Learning, Others), By Drug Type (Small Molecule v/s Large Molecule), By Application (Target Identification, In Silico Drug Design, Drug Development, Big Data Analytics, Others), By Diseases (Immuno-oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, Others), By End User (Pharmaceutical & Biotechnology Companies, Contract Research Organizations, Research Centers and Academic & Government Institutes), By Region, Forecast & Opportunities, 2025”, the global AI in drug discovery market is expected to witness robust growth during the forecast period on account of the increasing need to control the drug discovery & development process time and cost. Additionally, surging number of cross industry collaborations and partnerships are further expected to positively impact the growth of market over the next few years. Furthermore, rising adoption of cloud based apps and services is expected to propel the market through 2025. However, protecting intellectual property and data security & cyber threat issues can hamper the growth of market. Additionally, till date there is no AI inspired FDA approved drug in the market. This negatively impacts the growth of market. Moreover, lack of data sets and experts further impedes the growth of market. Besides, lack of government regulations and limited awareness about the technology further restricts the growth of market.
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The global AI in drug discovery market is segmented based on component, technology, drug type, application, diseases, end user, company and region. Based on component, the market can be bifurcated into software and services. The software segment is expected to dominate the market during forecast period. This can be accredited to the factors such as less cost and time to market the drug and low failure rate. Additionally, many software developers are making software for drug discovery and the strong demand for drug discovery software among the big pharma and biotechnology giants are anticipated to drive the growth of this segment over the next few years. Based on technology, the market can be categorized into machine learning, deep learning and others. The machine learning segment is expected to dominate the market since it helps in determining human body’s resistance to a drug type and resistance to combined drug therapies based on genotypic interpretations. Additionally, it helps researchers in using new computational algorithms for novel drug discovery. Based on drug type, the market can be divided into small molecule and large molecule. The small molecule segment is expected to dominate the market owing to its notable contribution towards many new drug application approvals. Based on application, the market can be fragmented into target identification, in silico drug design, drug development, big data analytics, prediction of study risks, patient matching and others. The target identification segment is expected to dominate the market over the next few years. This can be ascribed to the fact that the pharmaceutical industry is in a big crisis since most of the drugs are failing in the second stages of clinical trials due to wrong target or hit identification. AI understands the mechanism of a disease, establishes biomarkers, generates data and then identifies putative drug targets thereby increasing the chances of correct hit or target identification hence driving the growth of segment. Based on disease, the market can be grouped into immuno-oncology, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, others. The neurodegenerative diseases segment is expected to dominate the market owing to the ability of AI to discover drugs for complex conditions and growing emphasis of major players on providing AI based platforms for neurological diseases. Based on end user, the market can be segmented into pharmaceutical & biotechnology companies, contract research organizations and research centers and academic & government institutes. The pharmaceutical & biotechnology companies segment is expected to dominate the market until 2025, since AI allows companies to operate efficiently and sustainably improves the success rates at the early stages of drug development. The contract research organizations segment is expected to register significant growth in the market owing to the rise in research and production activity which ensures sustained demand for contract services.
IBM Corporation, Microsoft Corporation, Google Inc., NVIDIA Corporation, Pfizer, Merck, GSK, Novartis, AstraZeneca, Abbvie, Elli Lilly, Atomwise, Inc, Deep Genomics, Cloud Pharmaceuticals, Exscientia, Cyclica, Numerate, Envisagenics, OWKIN, Inc., Verge Genomics and others are some of the leading players operating in global AI in drug discovery market. The companies operating in the market are using organic strategies such as product launches, mergers and collaborations to boost their share. For instance, Microsoft launched a machine “Hanover” which can memorize available data & information required to treat cancer and predict combination of drugs for its diagnosis. Also, Exscientia has united with Celgene Corporation for drug discovery in oncology and autoimmunity. They have agreed to partner for three years to accelerate the discovery of small therapeutics drugs.
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“Asia-Pacific is expected to witness robust growth in the AI in drug discovery market during the forecast period, owing to the increasing healthcare expenditure and rising medical tourism in the region. Additionally, high internet penetration and cloud based services in the region is further anticipated to spur the market through 2025. Also, the key vendors operating in the market are expanding their business in the region creating lucrative opportunities for the growth of market.” said Mr. Karan Chechi, Research Director with TechSci Research, a research based global management consulting firm.
“Global AI in Drug Discovery Market By Component (Software v/s Services), By Technology (Machine Learning, Deep Learning, Others), By Drug Type (Small Molecule v/s Large Molecule), By Application (Target Identification, In Silico Drug Design, Drug Development, Big Data Analytics, Others), By Diseases (Immuno-oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, Others), By End User (Pharmaceutical & Biotechnology Companies, Contract Research Organizations, Research Centers and Academic & Government Institutes), By Region, Forecast & Opportunities, 2025”, has evaluated the future growth potential of global AI in drug discovery market and provides statistics & information on market size, structure and future market growth. The report intends to provide cutting-edge market intelligence and help decision makers take sound investment decisions. Besides, the report also identifies and analyzes the emerging trends along with essential drivers, challenges and opportunities in global AI in drug discovery market.