New legislation requiring pharmaceutical companies to implement 'serialization' is now coming into force. This means that no counterfeit product should enter the supply chain and no legitimate product is diverted from its intended destination. To work effectively, serialization requires a comprehensive system to track and trace the passage of prescription drugs through the entire supply chain. The application of track and trace principles can help to avoid counterfeit medicines from entering the supply chain. To be effective, digital technologies such as blockchain and RFID-enabled tag and trace systems need to be embraced.
This post was originally published on Quora, answering the question: "How do drug manufacturers select the right contract research organization(CRO)?"
Selecting the right contract research organization (CRO ) obviously depends on what activity is outsourced and with which regulations the outsourced processes need to comply. However, the following criteria certainly apply to pharma companies.
Typically, we would request evidence on how often the CRO has performed the activity, i.e., what their relevant experience is from a technical operation point of view. However, it is also very important to understand how they deal with Quality Assurance, Training, Disasters, and if they have been inspected by health authorities before, if upon inspection there were any critical findings, and how they managed these findings.
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 the healthcare sector in this post (diagnostics, medical applications of AI, digital health etc) -- those will be discussed in one of the future posts.
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.