Pharma Times - July, 2026 [Free Download]

We’re delighted to present the July 2026 Edition of Pharma Times.

As the global pharmaceutical landscape undergoes a profound transformation, computational intelligence has emerged as a primary engine driving healthcare innovation. Our theme for this issue, Pharma Intelligence: Rise of AI in Pharmaceutical Sciences, compiles insightful articles, expert perspectives, and forward-looking research that explore how artificial intelligence, machine learning, and data-driven algorithms are redefining every layer of the discipline.

Here's what awaits you in this issue:

1. Artificial Intelligence in Clinical Trials: Opportunities, Challenges and Future Directions: Insights into how machine learning optimizes protocol design, trial recruitment, and predictive analytics while addressing key implementation hurdles.

2. Artificial Intelligence and Machine Learning in B.Pharm Curriculum: A New Era of Pharmaceutical Innovation: An evaluation of modernizing foundational pharmacy education to equip future professionals with necessary computational skill sets.

3. The Algorithmic Therapist: AI’s Emerging Role in Mental Health Care: An exploration of therapeutic algorithms, digital interventions, and the opportunities and ethical considerations surrounding AI in psychiatric care.

4. The Impact of Artificial Intelligence on Pharmaceutical Practice : A perspective on how AI is revamping the various facets of the pharmaceutical sector.

5. Artificial Intelligence-Driven Pharmaceutical Services: A Review of Quality Indicators and Performance Metrics with a Focus on SERVQUAL Dimensions: A systematic review evaluating the quality, reliability, and performance metrics of AI-mediated pharmacy services.

6. The Role of AI and Neuroscience in Revolutionizing Personalized Education: An insightful examination of how integrating artificial intelligence with neuroscientific insights enables adaptive, bio-informed learning systems tailored to individual cognitive profiles.

7. Emerging and Future Technologies in Pharmaceuticals: Generative AI, Digital Therapeutics and AI–Bioconvergence: A forward-looking analysis of how generative models, digital therapeutics, and the convergence of biology and AI are shaping next-generation medicine.

8. When Worms Meet AI: The Future of Drug Discovery: An intriguing look at how combining high-throughput phenotypic screening in C. elegans with machine learning algorithms accelerates early target identification and drug testing.

9. An Industry-Integrated Postgraduate Diploma Model: From Classroom to Industry: A strategic framework for bridging academia-industry gaps through specialized hands-on training models.

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