Intelligent Effort – Quality in Drug Discovery

Guest commentary by Dr. Markus Henrich
There is a high demand for quality in daily life. Few of us would actively decide to forgo or ignore quality aspects during decision or selection processes. Consequently, most people immediately come up with mental pictures in the quality context. White sand and clear blue sea are frequently attributed to a quality vacation. Engine power and brand go along with the idea of a quality car. In the life science industry, quality is immediately linked with the “GxP” concepts, such as GMP or GLP.
Well, not in all areas of the life science industry. The exception is the discovery part of the business, upholding frequently a strict “GMP does not apply to us” position and painting a dark picture of choked creativity, suppressed by pointless rules and regulations. Of course, the discovery organisations have a point, the GxPs do not apply to them. Nevertheless, the significance of quality in drug discovery is hardly debatable which raises an important question: if the GxPs do not define the quality requirements of drug discovery, who does?Quality Definitions
The exclusion approach – “GMP does not apply” – is of course some kind of definition but obviously a bit limited in terms of what should be done. Even worse, it is easily interpreted as “rules do not apply at all”. This is a dangerous attitude, since no rules and no commitment quickly lead to quality anarchy.
Relevance of quality accepted, commitment to quality available but applicable rules are missing, another frequently observed situation in drug discovery. One common outcome of this are hectic activities – enthusiastic but uncoordinated, over- or under-shooting quality targets and quite frequently wasting resources in the process.
Overwhelming quality regulations but no commitment from the discovery team, the other extreme, leads to technocracy. Rules are defined and forced on discovery teams by faceless “governance units”, resulting in a predictable lack of acceptance and poor performance.

The sweet spot of drug discovery quality is obviously defined by adequate quality rules (but nothing beyond adequate!) in combination with real commitment on the side of the discovery team. Characteristics for this situation are efficacy (relevant (quality) targets are reached …) and efficiency (… with a minimum of effort and investment). Hitting this sweet spot requires some initial effort and reflection, some use of common tools like risk management and the application of a simple concept: quality is fitness for purpose.

Fitness for Purpose
The fitness for purpose concept focuses discovery teams on the (quality) demands of discovery projects. Activities or experiments within a project usually aim at achieving at least one project relevant purpose. Clearly, not every type of result is “fit for purpose”. Apart from having the desired value, the result needs to have a certain quality as well, normally described in terms like “correct” or “reliable”.
Bio assays for instance usually aim at the selection of development candidates. In order to avoid costly errors, assay results need to comply with certain quality attributes like adequate reproducibility. However, recent publications suggest significant room for improvement in this field (see The Economics of Reproducibility in Preclinical Research, Leonard P. Freedman et al, June 9, 2015, PLOS Biology).
In order to improve reproducibility, careful experimental design based upon scientific understanding is one prerequisite, smart use of basic quality processes is another. Changes of experimental conditions during project life time for instance clearly put reproducibility of results at risk. However, some changes will probably be unavoidable. Therefore, a defined quality process that tracks, evaluates and controls those changes (change management) is an obvious necessity. The same is true for documentation standards, error free data analysis, training of lab staff, storage and handling of reagents and so on.
The fitness for purpose concept leads quality considerations along a directed cascade of thought – project, experiment, purpose, quality attributes, quality process – starting at the scientifically relevant end of the business. Best qualified to follow this cascade of thought and to come up with meaningful quality processes are obviously the major contributors – the discovery team members themselves. This way, the resulting quality processes will be project and purpose oriented, scientifically relevant and they will make sense to the discovery team which leads to acceptance and compliance.

Seemingly pointless and frustrating quality governance (remember for instance the EU quality standards for cucumbers) is replaced with meaningful and accepted rules with a good chance to be applied with a high degree of commitment and with few if any mistakes. And, very important, “it is not GMP” – even so many of the self-developed rules and processes may be a reflection of those found in GMP guidelines. The difference between forced and self-defined is in this case a fundamental one.

Free of Purpose
“Science has gained most from all the unplanned results” is a much used argument against (over)regulation of discovery processes. Variability in experimental outcome compared to the original plan quite frequently adds more value to a project than the desired result would have done. While this is true, it does not argue the case against quality requirements for those unplanned results. Any result with dubious quality translates best case into “do it again”, worst case it leads to plain wrong decisions.

Dr. Markus Henrich
HENRICH Pharma-R&D Consulting
www.dr-henrich.com
post@dr-henrich.com

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