ANALYSING COMPLEX DATA IN THE PHARMACEUTICAL INDUSTRY: THE CASE FOR MULTIVARIATE ANALYSIS

When it comes to the Pharma supply chain, problems can occur at any part of the process, including non-standardized bills of material, translation mistakes, typos and poor proofreading, missed annotations, unclear briefs, artwork problems, expired digital assets, third-party artwork suppliers and printing shops. Consumer and pharma companies must also deal with a very strict regulatory environment. Each time there is a problem, the manufacturer risks having to issue a (potentially major) recall.

Not all eClinical applications are the same. For one thing, an eTMF, an EDC, and a CTMS all fulfill different functions. Perhaps more importantly, they are all built with varying degrees of complexity. The eTMF and EDC are both relatively simple applications in the IT world. Either can be introduced for a specific study or for a number of studies. If you’re unhappy with your eTMF or EDC applications, you can switch without too much fuss. The CTMS, on the other hand, is highly complex. It is the nerve center of the eClinical suite and is highly integrated with other software. It can be expensive to introduce, and its normal lifespan is more than 13 years. Therefore, once you install a CTMS, you will be committed for well over a decade. That’s why it is so important to choose your CTMS carefully and be armed with the best knowledge in order to do so. Which CTMS concept will be most functional: one where the entire eClinical suite comes from the same vendor or one where individual components are sourced from different vendors?

Drug innovation and the product pipeline in the cardiometabolic space is lagging due to the inherent time and cost of evidence generation needed for regulatory evaluation and approvals.

Artificial intelligence (AI) - “getting computers to do things that normally require a human mind” - is routinely being put to good use when making pharma clinical development decisions.