“If you don’t synthesize knowledge, scientific journals become spare-parts catalogues for machines that are never built.”Arthur R. Marshall
Right now, the pharmaceutical industry is facing a major hurdle to efficiency: when it comes to looking at the knowledge generated by a drug or disease state, it is extremely hard to see the full picture. And without seeing the full picture – laid out in sequence – any further assessment or analysis becomes risky; you may miss something crucial to your understanding.
It is difficult to see an overall view because information is too often siloed for different types of users. Safe Harbor prohibits much of the communication between commercial operations and Medical Affairs; publication planners may not be able to easily access the R&D work that has come before; regional affiliates may be presenting posters at meetings independent of headquarters.
Also, try to imagine the number of different entities that may study a compound or molecule throughout its lifecycle. From universities to biotech firms to large pharmaceutical companies and independent cohorts around the world, it’s often the case that knowledge about your target is generated by several institutions.
And when data is coming in from disparate sources, building a complete picture becomes extremely time-consuming. Whether that is collecting information from librarians, PubMed, Google Scholar, consultants or other entities to fill in the gaps, tracing the entire lifecycle of a molecule from discovery to prescription is a patchwork and laborious process.
It is necessary, then, to centralize, structure, and analyze all the relevant data points in sequence along the way, to look at the drug discovery process as a continuum, and to understand that this is often the difference between timely, valuable knowledge, and an educated guess.
The makeup of this continuum probably does not come as a shock to anyone in the life sciences business—we understand well that at every stage of the process lies a document. The first document that is produced is of course the grant for basic research. When a molecule is discovered, it is patented. Soon after it begins its journey through the clinical trials and real-world studies, from which presentations and posters are produced and shown at congresses. From there findings are published in a journal, labels are approved for prescriptions and eventually, based on the science that came before, treatment guidelines are written.
This sequence—grants, patents, clinical trials, presentations, publications, labels and treatment guidelines —is what I have termed the Medical Continuum.
By fitting these components of the Medical Continuum together, we can build fully referenced, verifiable confirmation and validation of the reasoning behind each stage of our knowledge development. This allows logical and structured analysis of relevant data, and analysis is the true value. We can look at any disease, any drug or mechanism of action, and see the whole picture, the warning signs… but also the successes.
The purpose of the Medical Continuum is to understand how content builds upon past content, how it is referenced and relied upon to deliver authentic analysis, and then turn that into actionable insights. This cannot be done if the knowledge is not sequential. Sequential knowledge provides a chain of evidence to support the analysis.
And without the context that this provides you, your research and scientific dissemination are prone to error. And error is the downfall of efficiency and further knowledge.