Artificial intelligence (AI) is mainly for the design a new drugs, finding new drug combinations and as well as deliver the clinical trials within minutes based on it. AI plays an important role in the disease identification, clinical trials research and drug discovery. Pharmaceutical industry can accelerate innovation by using technologies advancements. Generally, AI majorly stores a large amount of information and process it at a very high speed. A computer program with AI can answer the generic question it is meant to solve. Many big pharmaceutical companies investing in AI in order to develop better diagnosis or biomarker, to identify drug targets and to design new drugs and products. In March 2012, Merk partnership with numerate, focusing on developing novel small molecule drug which leas for CVS disease target. Robotics plays an active role in developing medical device. The production is highly regulated and developed by food and drug administration. Manufactures use robotics to minimize the cost. In December, 2016 Pfizer and IBM announced partnership to accelerate drug discovery in immuno-oncology. Mitsui and NVIDIA announce Japan's First Generative AI supercomputers for Pharmaceutical Industry. A recent paper in Nature reported that the integration of AI into the drug discovery and development increased by almost 40% in 2022. According to Global Genes, nearly 95% of rare disease don’t have FDA approved treatment or cures. Thanks to AI innovative abilities, the scenario is rapidly changing for the better. Artificial Intelligence (AI), in Drug Discovery Global Market, The market is expected to recover after the COVID-19 crisis at a great rate of about 43% and reach $1.1 billion through 2023.

1. ADVANTAGES, DISADVANTAGES
OF ARTIFICIAL INTELLIGENCE (AI),
CURRENT CHALLENGES & FUTURE ASPECTS
Submitted By: Prachi Pandey, Rahul Pal
M. Pharm (Pharmaceutics), IInd Sem.
In simple words AI defined as “The science and
engineering of making intelligent machines”.
- In future we will see the role of AI completely different
drug design, manufacturing and clinical trials etc.

2.  Artificial intelligence (AI) is mainly for the design a new drugs, finding new drug
combinations and as well as deliver the clinical trials within minutes based on it.
 AI plays an important role in the disease identification, clinical trials research and drug
discovery.
 Pharmaceutical industry can accelerate innovation by using technologies advancements.
 Generally, AI majorly stores a large amount of information and process it at a very high
speed.
 A computer program with AI can answer the generic question it is meant to solve.
INTRODUCTION

3.  AI is defines a more useful and more powerful computers.
 It also solving the new problems in another terms, it offers a new techniques to resolve unique
problems.
 Conversion of information into knowledge.
 Minimize the error: By reducing the risk enhance the chance to reach the accuracy with
more degree of precision.
 No break: Machines having programmed for long duration so do not required refreshment
and breaks.
ADVANTAGES OF AI

4.  High Costs: It’s requires huge costs as they are very complex machines and their repair and
maintenance requires huge cost.
 Difficult with software development- slow ad expensive.
 Few experienced programmers will required.
 Addiction: As we rely depends on machines to make everyday tasks more efficient we use
machines.
 Difficulty in investigation: Usefulness of artificial and robotics have difficulty in the
process.
DISADVANATAGES OF AI

5.  Many big pharmaceutical companies investing in AI in order to develop better diagnosis or
biomarker, to identify drug targets and to design new drugs and products.
 In March 2012, Merk partnership with numerate, focusing on developing novel small
molecule drug which leas for CVS disease target.
 Robotics plays an active role in developing medical device. The production is highly
regulated and developed by food and drug administration. Manufactures use robotics to
minimize the cost.
 In December, 2016 Pfizer and IBM announced partnership to accelerate drug discovery in
immuno-oncology.
CURRENT CHALLENGES/FUTURE WITH AI

6.  Molecular target prediction.
 Protein structures to predict drug molecule
interaction and drug bioactivity.
 Treatment and diagnosis of patients.
 Activity prediction like; Physicochemical properties
and ADMET properties.
 Drug Discovery, Development and Clinical Trials.
VARIOUS APPLICATIONS OF AI

7.  Mitsui and NVIDIA announce Japan's First Generative AI supercomputers for
Pharmaceutical Industry.
 A recent paper in Nature reported that the integration of AI into the drug discovery and
development increased by almost 40% in 2022.
 According to Global Genes, nearly 95% of rare disease don’t have FDA approved treatment
or cures. Thanks to AI innovative abilities, the scenario is rapidly changing for the better.
 Artificial Intelligence (AI), in Drug Discovery Global Market, The market is expected to
recover after the COVID-19 crisis at a great rate of about 43% and reach $1.1 billion
through 2023.
CONCLUSION