Pharmaceutical ("Pharma") and Biotech

The Pharmaceutical and Biotech industry is facing a steep challenge in bringing new products to market due to patent cliff combined with shrinking pipelines and longer Clinical Trials for new therapies. New Drug Discovery now takes longer than ever and it is far more expensive and carries greater risk of failure in the late stage.

These factors have led Pharma companies to look at increasing collaboration within and outside the organizations creating a necessity to share valuable Research Information without compromising on either agility or Data Security. New breed of Scientists look to adopt innovative technologies to model new molecules leveraging Genomic Data and the Research Data that is meticulously captured need to be made accessible to support Scientific decisions. These factors have led Research Information Technology - IT leaders to recognize the need to modernize and optimize current technology portfolio to support the new research paradigm with minimal disruptions to core research.

Improved Pharmaceutical Information Technology - IT Prognosis

Technology now drives pharmaceutical innovation, but also introduces complexity. At ITS, we’re committed to helping Pharma companies streamline key processes, secure critical data and solve complex service issues.

The Increasing use of Artificial Intelligence - AI In the Pharmaceutical Industry

The pharmaceutical industry has long relied on cutting edge technologies to help deliver safe, reliable drugs to market. With the recent pandemic, it’s proved more important than ever for pharmaceutical companies to get drugs and vaccines to market faster than ever before.

Artificial intelligence and machine learning have been playing a critical role in the pharmaceutical industry and consumer healthcare business. From augmented intelligence applications such as disease identification and diagnosis, helping identify patients for clinical trials, drug manufacturing, and predictive forecasting, these technologies have proven critical. On a recent episode of the AI Today podcast Subroto Mukherjee, who is Head of Innovation and Emerging Technology, Americas at GlaxoSmithkline Consumer Healthcare discussed how AI and ML are being applied to the pharmaceutical industry and some unique use cases for AI and ML technology. In this follow up interview he shares his insights in more detail.

How is Artificial Intelligence - AI currently being applied in the Pharmaceutical Industry?

Artificial Intelligence - AI, Machine Learning - ML and Deep Learning have been critical in the Pharmaceutical Industry and consumer Healthcare business. Artificial Intelligence - AI, Machine Learning - ML and Deep Learning are playing an important role during this pandemic, driven by COVID-19 Coronavirus Pandemic, and the race to discover effective vaccines. The top-level uses in Pharma and Consumer Healthcare arena as follows:

• Disease Identification/Diagnosis – It can range from oncology to COVID-19 to degeneration in the eyes.
• Digital Therapeutics / Personalized Treatment/Behavioral Modification; This can be effectively used to assist and identify individuals to provide early insight into the condition – such as gum condition, accurately classify cutaneous skin disorders, suggest primary treatment options with Over-the-counter medication, and serve as an ancillary tool to enhance the diagnostic accuracy of clinicians, or improve educational and clinical decisions made by your child's teacher, or your mental health professional or even your medical doctor.
• Drug Discovery and Manufacturing: It helps in the initial screening of drug compounds to the predicted success rate based on biological factors.
• Measuring RNA, DNA quickly. Precision medicine or next-generation sequencing helps in the faster discovery of drugs and tailored medication for individual patients.
• Predictive Forecasting – Predicting an epidemic is one of the key examples of this topic. ML and AI technologies are also being applied to monitoring and predicting epidemic outbreaks or seasonal illnesses worldwide. A predictive forecast helps plan our supply chain to get the inventory at the right time and the right quantity based on the predicted intensity.
• Clinical Trials – Identifying the right candidate for the trial based on history and disease conditions, and additional attributes, overlaying with infection rates, demographics, and ethnicity to represent the most impacted.
• Apart from the Healthcare conditions, we see many AI ML usage in Digital Transformation areas for Pharma and Healthcare companies such as Martech, AdTech, Supply Chain, Sales, and Customer Service.