Digi-Tech Pharma & AI 2026

Schedule

Wed, 27 May, 2026 at 09:00 am to Thu, 28 May, 2026 at 06:00 am

UTC+01:00

Location

Copthorne Tara Hotel London Kensington | London, EN

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The Digi-Tech Pharma & AI 2026 Conference is a leading platform uniting pharmaceutical and technology leaders healthcare innovators regulatory authorities and solution providers to explore the evolving digital landscape in pharma. This conference promotes collaboration and knowledge exchange enabling organizations to embrace innovation streamline operations and drive better patient outcomes.


This event serves as a dynamic platform to explore the integration of science and technology within the pharmaceutical industry with a strong emphasis on digital trends AI and machine learning digital health ecosystems collaborative innovation and patient-centric drug development. Key focus areas include digital drug discovery clinical trials data science big data informatics real-world data and evidence and emerging innovations in digital health.


Discover how digital innovation is transforming the pharmaceutical lifecycle - from accelerating development and streamlining regulatory processes to delivering more personalized accessible and efficient therapies for patients around the world


At Business we bring together the brightest minds leaders and trailblazers from across industries to explore the latest trends technologies and strategies shaping the future.


Connect with professionals decision-makers and innovators from across the sector to expand your network and build lasting relationships.


Gain valuable insights from thought leaders as they share strategies real-world experiences and forward-thinking perspectives.


Conference Link: https://corvusglobalevents.com/conference/digi-tech-pharma-ai 


Registration Link: https://corvusglobalevents.com/digi-tech-pharma-ai/registration 


Key Highlights:

  • Digital Technology Trends in the Pharma and Biotech Industry
  • Adopting AI and Machine Learning to unlock the full potential of Pharma
  • Integrating Pharma into the Digital Health Environment
  • Collaborative Innovation: Finding the right partners to leverage new technologies in Pharma
  • Patient-Centred Drug Discovery
  • Implementing FAIR Data Principles in Pharma R&D
  • Harnessing Data Science for Drug Combination Discovery
  • AI + Big Data: The Future Growth Formula
  • Clinical Data Interpretation with AI Tools
  • Big Data Applications in Precision Medicine
  • Multi-omics Integration and Advanced Data Analytics
  • Translational Medicine Data: Integration and Visualization
  • Data and Healthcare Analytics for Smarter Decisions
  • The Growing Role of Real-World Data in Pharma
  • RWD in Clinical Research and Drug Development
  • RWE & RWD in Regulatory Decision-Making
  • Using Real-World Data Science to Improve Patient Care
  • Best Practices in Real-World Data Governance
  • Applying AI to the Design of Lead Compounds
  • Algorithms and Models for Drug Discovery
  • Target Identification & Validation Using AI/ML
  • Quantum Computing for Advanced Drug Discovery
  • Genomics and Drug Discovery
  • Virtual and Hybrid Clinical Trials
  • R&D Use Cases and Case Studies
  • Healthcare & MedTech Advancements
  • IoT Adoption in the Pharmaceutical Sector
  • Cloud Computing Potential in Pharma
  • The Impact of Digital Health on Drug Development
  • Digital Health Strategies for Patient-Centric Clinical Trials
  • Convergence of Digital Therapeutics and Pharma
  • Pharma-HealthTech Collaboration to Enhance Patient Experience
  • Blockchain and AI-Based Platforms for Drug Development
  • Evolving Regulatory Frameworks for Digital Pharma
  • AI/ML Regulatory Compliance: Challenges & Approaches
  • Ensuring Data Privacy Integrity and Cybersecurity in Digital R&D
  • Ethical Considerations in AI-Driven Drug Discovery
  • Digital Audit Trails and GxP Compliance
  • Trust Transparency & Governance in Pharma’s Digital Transformation




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Where is it happening?

Copthorne Tara Hotel London Kensington, Scarsdale Pl, London W8 5SY, United Kingdom, London

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