Abstract
Quantitative assessment of metabolites of drug candidates in early-phase clinical development presents an analytical challenge when methods, standards and assays are not yet available. Radioisotopic labeling, principally with radiocarbon (14C), is the preferred method for discovering and quantifying the absolute yields of metabolites in the absence of reference material or a priori knowledge of the human metabolism. However, the detection of 14C is inefficient by decay counting methods and, as a result, high radiological human 14C-doses had been needed to assure sensitive detection of metabolites over time. High radiological doses and the associated costs have been a major obstacle to the routine (and early) use of 14C despite the recognized advantages of a 14C-tracer for quantifying drug metabolism and disposition. Accelerator mass spectrometry eliminates this long-standing problem by reducing radioactivity levels while delivering matrix-independent quantitation to attomole levels of sensitivity in small samples or fractionated isolates. Accelerator mass spectrometry and trace 14C-labeled drugs are now used to obtain early insights into the human metabolism of a drug candidate in ways that were not previously practical. With this article we describe some of our empirically based approaches for regualted bioanalysis and offer perspectives on current applications and opportunities for the future.
Financial & competing interests disclosure
Stephen R Dueker, Peter N Lohstroh, Jason A Giacomo, Le T Vuong, Bradly D Keck are employees of Vitalea Science, who fund their authorships. John S Vogel is an unpaid advisor to Vitalea Science but possesses shares of the Company. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
Acknowledgements
The authors thank Saira Abidi and Mekonen Teame for technical support in the generation of some of the data. The authors also thank Linda Palagi-Lynn for providing input on quality assurance and best practices for regulated bioanalysis.
Notes
‡Timing for the development of plans, reports and training are not specified.