APAC to Witness Robust Growth in AI in Drug Discovery Market over the Next Five Years
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.
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