Subscribe Become an Author Log In

BiopharmaTrend.com

Covering emerging technologies, innovations, and companies

Biopharma Insights


Top AI in Pharma and Healthcare Conferences in 2020 You Can’t Miss

   by Andrii Buvailo    9737
Top AI in Pharma and Healthcare Conferences in 2020 You Can’t Miss

Artificial intelligence (machine learning and deep learning, to be more specific) has become widely discussed topics in the area of life sciences and healthcare over the last several years and the excitement keeps growing. While a lot of pharmaceutical companies and healthcare organizations express considerable interest in possible new opportunities, associated with the use of artificial intelligence for early drug discovery, clinical trial optimization, and business intelligence, a considerable gap still exists when it comes to understanding new technologies by pharmaceutical professionals and leaders. The key questions here are these:

  • What machine learning / AI can and can’t do for the pharmaceutical industry

  • What should be done to harness practical and measurable value out of machine learning / AI?

  • How it should be done and what are the timelines for getting returns on investments? 

The Overview of AI in Drug Discovery in 2019: The “Proof-of-concept Year”

   by Andrii Buvailo    979
The Overview of AI in Drug Discovery in 2019: The “Proof-of-concept Year”

The race for adopting new machine learning (ML), deep learning (DL) and related technologies (for simplicity -- “artificial intelligence”/”AI”) keeps rapidly unfolding in the pharmaceutical industry, albeit with varying rate of progress across different use cases

Let’s review retrospectively some of the key developments in the drug discovery area in 2019 and see how they characterize the current state of AI in the pharmaceutical industry (“hype vs reality”). Note, that I do not cover healthcare sector in this post (diagnostics, medical applications of AI, digital health etc) -- those will be discussed in one of the future posts.

 

Becoming Pharma 4.0: How Digital Transformation Is Reshaping Pharmaceuticals

   by Tim Sandle    846
Becoming Pharma 4.0: How Digital Transformation Is Reshaping Pharmaceuticals

The digital transformation of biopharmaceutical manufacturing is continuing at a rapid pace as companies attempt to mine the sources of data available. Innovations include predictive analytics, big data analytics, and creating the digital plant. Digital transformation offers a mechanism to revise its business model, to improve production processes, to design new drugs faster by using artificial intelligence to screen compounds and to increase responsiveness to customers. Furthermore, the volume of data processed by pharmaceutical firms shows no sign of slowing down. This means pharmaceutical companies must act quickly in terms of building core internal digital capabilities and moving beyond their traditional IT functions to all areas of the business.

 

The Evolution Of Pharmaceutical R&D Model

   by Andrii Buvailo    832
The Evolution Of Pharmaceutical R&D Model

There is a plethora of analytics reports, including ones by Deloitte, DKV Global, and Ernst and Young, all pointing out to a declining business performance of the pharmaceutical industry. They all convey a similar bottomline message: the decline is not due to a lack of innovation (the innovations are growing). And not because sales are falling or markets are shrinking (revenues are growing in general, and the markets are expanding with the expanding and ageing population). The key reason of the declining financial performance is the fact that research and development (R&D) costs are growing substantially faster over an average investment period, than the actual revenues over the same period. This kills operational profits, leading to a decline in the overall business gain. A direct consequence of that -- an increasingly stagnating industry, cutting sometimes promising R&D programs, jobs etc.  

There are two more relevant questions here: 

1) why R&D costs are growing faster than revenues, considering that technological progress is seemingly providing more and more optimal and powerful technologies to pharma companies at a constantly decreasing specific price (e.g. costs of computation, sequencing, screening and many other things are falling), and 

2) what to do about it to reverse the decline in pharma industry performance?