On building bridges

Innovation occurs when we see what no one else sees

Reflections on identifying and realizing opportunity

Biology is a gambler

"Medicine is a science of uncertainty and an art of probability"        William Osler
Biology is inherently probabilistic. This is equally true of human biology and medicine. Although clinical training involves numerous diagnostic flow charts, therapeutic algorithms etc. that are often presented as being built on deterministic "if-then" couplings clinical practice teaches otherwise. Some patients will indeed respond or present as the textbook proposes, but not all. Absolutes such as always and never are rarities in medical practice.  A qualifying vocabulary of terms such as mostly, generally, usually, commonly, frequently, for the most part or conversely rarely, occasionally, infrequently tends to be more appropriate and less contentious when dealing with the variability and uncertainty that accompanies medicine in the real world.
If this premise is accepted, then acumen in understanding, interpreting and responding to probabilities is essential to the practice of medicine and in extension clinical research and drug development. A fundamental understanding as to what probability is, is critical. William Briggs in his book "Uncertainty: The soul of Modeling, Probability and Statistics" proposes that uncertainty is in essence ignorance. Probability quantifies the ignorance.
Janet Woodcock from FDA expands in the context of pharmaceutical medicine:

"When a regulatory decision is made, uncertainty can remain about many aspects of a new drug’s performance, said Janet Woodcock, Direc-
tor, Center for Drug Evaluation and Research (CDER), FDA. As a result, she noted, uncertainty is “central to the evaluation of data,” and can affect our understanding of both benefits and risks. Uncertainty in the drug review process has many sources, all of which, she noted, must be analyzed, quantified to the extent possible, judged, and communicated responsibly (see Box 1-3). FDA’s goal is to bring the best possible science to bear on these tasks, in order to ensure that stakeholders and the public have a clear understanding of both the available evidence and the pending uncertainties, and that stakeholders understand that both evidence and uncertainty are important factors in any given regulatory decision"

Page 5: IOM (Institute of Medicine). 2014. Characterizing and communicating uncertainty in the assessment of benefits and risks of pharmaceutical products: Workshop summary. Washington, DC: The National Academies Press

Competency in understanding and dealing with uncertainty, respectively probabilities, conditional on situation and circumstance  is thus a necessary skill in clinical research and development. Extending the dictum attributed to Donald Rumsfeld what we know that we know, what we know that we don't know, and what we don't know that we don't know, is an inherently probabilistic trilogy, which evolves in terms of content (what it is that we know ....) and in terms of the confidence we hold (how sure / unsure we are).
Steven Goldberg in his foreword to the book by William Briggs contends "probability does not have an existence in reality". He goes on "all probability is conditional on evidence and resides in the mind". This inherent subjectivity of probability (in line with Bayesian thinking) brings with it numerous challenges and may be perceived as unscientific. However,  herein lies a highway to opportunity, to recognize and accept that probability concerns relationships between propositions that describe our perception of the natural world, which as Steven Goldberg notes "probability is epistemologically conditional ... does not exist in ontological reality,  but in the epistemology of the mind..", (Page viii) or more colloquially our perception (evidence) is our reality (mind). How evidence is perceived, influences the reality it creates.
In the quest to build bridges to opportunity this has two important implications: 1) changing perceptions (the interpretation and understanding of evidence) can change realities (uncover hitherto undiscovered opportunities) and 2) probability is subjective giving credence to the Bayesian approach for dealing with evidence.  The latter is unsurprising if the assertion that probability quantifies ignorance is accepted. Ignorance is frequently personal: another may know and understand what I do not and thus be less ignorant than I, leading to differences in presumed probabilities. Insider trading is a case in point!