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ADVANTAGES, DISADVANTAGES
OF ARTIFICIAL INTELLIGENCE (AI),
CURRENT CHALLENGES & FUTURE ASPECTS
Submitted By: Rahul Pal Prachi Pandey Submitted To: Mr. Abhishek Tiwari
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.
 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
 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
 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
 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
 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
 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

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Advantages disadvanatges of AI in Pharmaceuitcal Industry.pptx

  • 1. ADVANTAGES, DISADVANTAGES OF ARTIFICIAL INTELLIGENCE (AI), CURRENT CHALLENGES & FUTURE ASPECTS Submitted By: Rahul Pal Prachi Pandey Submitted To: Mr. Abhishek Tiwari 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

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