PharmTech: High-potency drugs, including antibody-drug conjugates (ADC), are an important area of drug development. How does analytical testing differ between an ADC and an isolated cytotoxic small molecule?
Hayes: The ADC is a heterogeneous mixture containing a cocktail of monoclonal antibodies with different drug payloads. Because of this heterogeneous nature, ligand-binding assays (LBAs) are generally used for ADC bioanalysis. Their mass spectrometric characterization has been performed by using matrix-assisted laser desorption ionization (MALDI) time-of-flight instruments (1) and more recently by using liquid chromatography-mass spectrometry (LC-MS) with electrospray ionization coupled to time-of-flight or triple quadrupole mass detectors (2, 3). An important assessment of ADCs is the determination of the average number of drugs that are conjugated to the antibody that is the payload. The drug- to-antibody ratio (DAR) is most normally performed by using hydrophobic interaction chromatography (HIC) (4).
PharmTech: What are some challenges in bioanalytical testing for highly potent drugs and how are they overcome?
Hayes: Beyond throughput and quantitative sensitivity is the requirement for accurate and reliable data. The parameters that must be in control are described in EMA and FDA guidelines as well as whitepapers (5-8). The analyst must be well trained to ensure reliable conduct of the assay. Liquid-handling automation is the easiest way to mitigate assay variability and increase efficiency (9).
Optimized sample-preparation techniques that provide high enrichment factors become critical for dilute concentrations of high-potency drugs. Solid-phase extraction (SPE) is a common technique for sample extraction in bioanalysis. High-efficiency sorbents and novel 96-well plate designs, including SPE pipette tips and discs, offer solutions to elute drugs in very small volumes. Moreover, mixed-mode or charge-exchange sorbents provide even cleaner sample extracts (10, 11). Also, columns packed with sub-2 µm stationary phase particles are perhaps one of the most significant contributions to improving bioanalysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS)(12).
In addition, fused-core silica particle technology continues to unlock opportunities for developing higher throughput assays (13). When conventional bioanalytical platforms do not have sufficient sensitivity, some investigators turn to accelerator mass spectrometry (AMS) to measure the drug (14). AMS can deliver 1000-fold improvement in sensitivity compared to most LC-MS/MS methods.
PharmTech: What are some recent technology advancements used in testing highly potent drugs?
Hayes: Newer LBA platforms centered on electrochemiluminescence or fluorescence (15) have become platforms of choice because of their inherent ability to increase assay sensitivity and broaden the dynamic range of the assay. Moreover, some ultra-sensitive platforms and label-free enzyme-linked immunosorbent assay (ELISAs) are now available. For example, the immuno-polymerase chain reaction (PCR) platform (IPCR) approach links standard immunoassays with the exponential signal amplification of PCR, thereby increasing conventional immunoassay sensitivity 100 to 10,000 fold.
Predictive models for toxicity continue to be developed. The typical approach is to correlate in vivo (animal) plasma concentration versus time and toxicity curves to in vitro concentration versus toxicity response curves for a large number of compounds and then define a mathematical relationship between the animal response data and the in vitro response data (16). The challenge that remains is the accuracy of translating in vitro toxicity into meaningful in vivo effects. An alternative approach is to define toxicity biomarkers that are translatable between nonclinical species and patients. The Predictive Safety Testing Consortium, a precompetitive collaboration of pharmaceutical companies and FDA, has formed various working groups to address the challenges associated with the development and qualification of translatable biomarkers of toxicity (17).
1. A. Safavy et al., Bioconjugate Chem. 14 (2) 302-310 (2003).
2. J.R. Junutula et al., Clin. Cancer Res. 16 (19) 4769-4778 (2010).
3. A.C Lazar et al., Rapid Commu. Mass Spectrom. 19 (13) 1806-1814 (2005).
4. K.J. Hamblett et al., Clin. Cancer Res. 10 (20) 7063-7070 (2004).
5. B. DeSilva et al., Pharm. Res. 20 (11) 1885-1900 (2003).
6. J. Lee et al., AAPS J. 9 (2) E164-170 (2007).
7. M. Kelley et al., AAPS J. 9 (2) E156-163 (2007).
8. R.W. Abbott et al., Bioanalysis 3(8), 833-838 (2011).
9. A.B. Ahene et al., AAPS J. 14 (1) 142-153.
10. J.X. Shen et al., J. Chromatogr. B. 843 (2) 275-282 (2006).
11. J.X. Shen et al. Rapid Commu. Mass Spectrom. 21 (18) 3145-3155 (2007).
12. L. Tolley et al., Anal. Chem. 73 (13) 2985-2991 (2001).
13. R.D. Ricker et al., Chromatogr. Sci. 46 (3). 261-268 (2008).
14. A. Arjomand., Bioanalysis 2 (3) 519-541 (2010).
15. J.R. Mora et al., Bioanalysis 2 (10) 1711-1715 (2010).
16. J.M. Jr. McKim., Comb. Chem. High Throughput Screening 13 (2)
17. E. H. Dennis et al., Drug Dev. Res. 74 (2) 112-126 (2013).