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SMALL MOLECULE DRUG DISCOVERY MARKET ANALYSIS

Small Molecule Drug Discovery Market, By Therapeutic Area (Oncology, Central Nervous System, Cardiovascular, Respiratory, Metabolic Disorders, Gastrointestinal, Others), By Process (Target ID/Validation, Hit Generation and Selection, Lead Identification, Lead Optimization), By End User (Pharmaceutical Companies, Biotechnology Companies, Contract Research Organizations (CROs), Academic and Research Institutes, Others), By Geography (North America, Latin America, Asia Pacific, Europe, Middle East, and Africa)

  • Published In : Aug 2024
  • Code : CMI5214
  • Pages :165
  • Formats :
      Excel and PDF
  • Industry : Pharmaceutical
Market Challenge - Stringent regulatory requirements

Global small molecule drug discovery market growth can be hampered due to stringent regulatory requirements imposed by regulatory authorities around the world. Compliance with regulations has become a complex and costly affair for pharmaceutical companies. Obtaining regulatory approval for new drug candidates involves rigorous clinical testing on humans which is a long, expensive and risky process. Any changes to manufacturing processes or facilities are also closely scrutinized. Non-compliance can delay drug launches and incur huge financial penalties.  The approval timelines have also become longer. Meeting all regulatory norms prescribed by different countries can hamper the market growth. Such stringent regulatory environment has increased the research and development costs and time for drug developers.

Market Opportunity: Adoption of artificial intelligence

Rising adoption of artificial intelligence can offer growth opportunities for global small molecule drug discovery market players. AI and machine learning algorithms can help analyze huge datasets to identify new drug targets and molecules at a fraction of the traditional cost and time. Companies are increasingly utilizing AI throughout the drug discovery workflow from target identification and validation to lead optimization. It helps expedite the discovery process and reduces risks of failure in later stages. The ability of AI to sift through massive chemical libraries and clinical trials data is empowering researchers. AI may help address the industry’s pressing need to boost productivity and bring more drugs to the market overcoming stringent regulations. Its potential to streamline operations and enhance efficiency provides significant growth avenue for stakeholders.

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