McCague Scientific Consulting

Pharmaceutical Pipeline Profiling

The profiling of the relationships between the chemical structures of pharmaceutical agents and their therapeutic areas and clinical pipeline progression can give useful insight for decision-making concerning drug design and development and supporting technology. For this purpose, a proprietary database has been built over the past fourteen years with over 10,000 entries covering pharmaceutical entities in the clinical pipeline or launched, including over 4,000 structures. It includes information from the pipelines of more than 1,000 pharmaceutical companies.

Principal fields of the database are (i) the clinical phase,(ii) the therapeutic sector, and (iii) the structure type. About 2800 of the entries relate to compounds undergoing clinical trials, about 1700 are launched drugs and the rest have dropped from development. The status of compounds said to be in clinical development is checked regularly to ensure that the database reflects the current situation and not just the 'highest clinical phase reached'. Therapeutic sectors are infection, inflammation, oncology, neurology, cardiovascular and genetic/miscellaneous diseases. Consideration of the relationships between chemical structures of drugs in the different areas may facilitate the repurposing of drugs to application in a different therapeutic area. The structure types include both small and large molecule drug candidates. The large molecules cover biologics like antibodies and cell-based therapies, vaccines, oligopeptides and oligonucleotides. For the small molecules these are classified according to the chirality; that is mostly as (i) synthetic and achiral, (ii) synthetic and chiral, or (iii) chirality of a natural product source. These classifications make the database valuable to assess the application of chiral chemistry technologies.

A particular feature of the database is that clinical events have been recorded; this allows determination of the rates of clinical success for any chosen category. Thus in respect of clinical Phase 1 for example, it is recorded when an entity progresses to Phase 2 or when an entity ceases development after Phase 1. The success rate for Phase 1 is then given by 100% x [number of progressions into Phase 2]/ [number of all Phase 1 events]. Likewise the success rates for other clinical phases may be computed. Overall clinical success rates work out as Phase 1 = 46%; Phase 2 = 31%; Phase 3 = 55%, NDA = 92%; entire pipeline = 7.2%, but are dependent on for example the therapeutic area. Entire pipeline success rates decrease in the order: Genetic diseases/miscellaneous (12.5%) > Infection (10.1%) > Oncology (8.0%) > Inflammation (6.9%) > Cardiovascular (6.3%) > Neurology (3.7%). By knowing the clinical success rate associated with a particular category may be valuable for investment decisions.

McCague Scientific Consulting