Introduction
In past decades, innovation in biotherapeutics has led to significant advances in the biopharmaceutical industry. These medicines are similar in structure to molecules produced naturally in the human body and can seek out highly specific targets in their treatment of disease. As a result, they hold promise in treating a range of acute and chronic conditions.
One highly successful class of biotherapeutic drugs uses monoclonal antibodies (mAbs), complex proteins that have a proven therapeutic effect for the treatment of cancer.1 Depending on their design, these proteins can perform a range of valuable functions including blocking cell growth, preventing immune system inhibition, driving the destruction of cancer cell membranes, reducing blood supply to cancer cells, delivering chemotherapeutic agents to defected cells while avoiding healthy cells, and more. By mimicking the activity of antibodies found naturally in the body, mAbs can bind to targeted antigens, thus flagging them for removal, or can be used in diagnostic studies aiming to detect and quantify the presence and prevalence of antigens.
During preclinical analysis, a pharmaceutical organization may have a dozen mAb candidates to assess. The evidence gathered at this stage must allow for the go or no/go decision for a given candidate therapeutic, to reduce risk of failure at a later development stage and save significant costs. In parallel, the organization must develop the proof points needed to demonstrate that the candidate will have the desired therapeutic effect in the human body without dangerous side effects or health consequences.
From Promising Candidate to Effective Therapeutic
The preclinical analysis must be accurate, sensitive, selective, and robust to obtain the high-quality pharmacokinetic, pharmacodynamic, and toxicokinetic data needed to reliably inform and enable important drug development decisions, and accelerate the right candidate through the pipeline.
Ligand binding assays (LBAs) have traditionally been labeled the ‘gold standard’ in therapeutic bioanalysis. LBAs are typically sensitive and selective, as they utilize highly specific antibodies in their implementation. However, it is cost-ineffective and time-consuming to generate different antibodies for each biotherapeutic candidate. LBAs can also suffer from matrix interference, with other sample components – such as endogenous molecules similar to the analyte itself – interfering with analysis. This vulnerability introduces potential risk when transferring the method between matrices.
LBA limitations have led to the emergence of immuno-mass spectrometry (immuno-MS) as an alternative method of analysis, which combines the capabilities of LBA and MS to improve the sensitivity and selectivity of these bioanalytical techniques. Whilst conventional sample preparation methods for immuno-MS can be labor-intensive and slow, recent advanced methods are minimizing such limitations, and accelerating and simplifying the universal bioanalysis of mAb therapeutic drugs at the preclinical phase.2 This not only saves time during analysis but also enables organizations to more accurately and confidently assess the probability of drug development success earlier in the pipeline.
The Need for Data in Supporting the Development of Successful mAb Biotherapeutics
Biotherapeutics – including recombinant proteins and hormones, cytokines, growth factors, vaccines, and many other types of complex biomolecules – have accounted for almost half of drug approvals in recent years. Within this class, mAbs are the most rapidly growing molecule type for oncology, anti-immunity, and chronic inflammatory diseases.3 An especially active subclass of mAbs is found in immunoglobulin G subclass 1 (IgG-1) antibodies, which are the most common subclass used for oncology, and can be structurally modified to increase therapeutic efficacy while reducing potential side effects.3
To develop a successful mAb biotherapeutic, pharmaceutical organizations seek to identify a selective and potent molecule to perform a given task in the human body. To achieve this, laboratories must make timely, confident decisions at early stages of development – for which they need accurate and reliable quantitative bioanalysis of a substance’s pharmacokinetics and pharmacodynamics (how a drug will be absorbed or metabolized in the body over time, for instance). Given that just one in 5,000 preclinical candidates (inclusive of chemically synthesized small molecules and biological entities) is estimated to reach the commercial market4 – and considering the cost, regulatory and ethical risks, and time delays accrued by progressing a candidate that fails – achieving precise, reliable preclinical screening is a matter of priority for the pharmaceutical industry.
Overcoming the Challenges of Conventional Bioanalysis
LBAs, such as enzyme-linked immunosorbent assay (ELISA), are a leading method of biotherapeutic analysis. These plate-based assay techniques bring high sensitivity and throughput, but unfortunately suffer from limitations.
In its simplest form, an ELISA comprises a multi-well plate of numerous sample antigens, to which a mAb is applied and allowed to bind. To perform successfully, an ELISA requires the generation of specific, high-quality antibodies with specificity to the target antigen, which can take a great deal of time and resources to develop. The method is also sometimes limited in linear dynamic range as it quickly becomes saturated over the drug profile, and can, therefore, be inadequate to meet pharmacokinetic requirements without being recalibrated and run multiple times. Furthermore, alongside their aforementioned sensitivity to matrix interference, LBAs are highly susceptible to anti-drug antibodies in animal studies, raising concerns around the method’s ability to pick out an analyte of interest from the copious other constituents of a sample.
Based on advances in targeted proteomics technology, strategies based on liquid chromatography-mass spectrometry (LC-MS) have emerged as a promising way forward for bioanalysis. One of the most common methods for protein quantitation by LC-MS is an approach based on surrogate peptides, by which intact proteins are digested and broken down into smaller, easier-to-analyze peptides. Appropriate peptides are then chosen as a surrogate measure for the protein and monitored via either triple quadrupole or high-resolution MS. However, identifying a single low-level peptide within a protein-filled sample – and differentiating between highly similar peptides – remains challenging. Also, the sample preparation procedures for surrogate peptide LC-MS may be an obstacle to achieving the sensitivity required for precise and complete quantitation at the low levels required.
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Hybrid methods that unite LBA and MS (immuno-MS) bring the best of both worlds to bioanalysis by combining the specificity of LBA and the powerful and specific detection techniques of MS. Immuno-MS provides unparalleled selectivity and sensitivity and offers a swift, streamlined universal method for preclinical bioanalysis of mAb therapeutics.2
Accelerated Drug Development with Advanced Immuno-MS
At the preclinical stage, methods of bioanalysis for biotherapeutics must be robust, reproducible, and able to capture a humanized mAb of interest from an animal sample (a humanized mAb being a non-human antibody with a modified protein sequence to optimize its similarity to naturally occurring antibody variants in humans). Given the potential of immuno-MS, numerous pharmaceutical and contract research organizations are opting for this technique in their preclinical analysis of mAb therapeutic candidates. With immuno-MS, targeted molecules are extracted from a sample using immunoaffinity chromatography, during which biomolecules are separated based on their specific binding interactions with another substance: in this case, antibody and antigen. Targets are then digested (for peptidebased quantitation) and analyzed using MS.
Immuno-MS has proven beneficial in the case of preclinical analysis of IgG-1 type mAbs.2 The high precision, selectivity, and sensitivity of the technique facilitate earlier and more precise identification of drug candidates that are likely to fail later in the drug development process, enabling organizations to abide by the principle of ‘fail fast, fail cheap’. By identifying areas in which investment may be wasted, and, conversely, areas in which it could lead to the most successful outcome, drug developers can maximize their chances of success at preclinical and even earlier points in the pipeline. As a result, organizational profitability and reputation can be protected.
Advances in speed and simplicity through automated, bead-based enrichment and digestion have enhanced the application of immuno-MS by removing numerous time-consuming and error-prone manual steps from such workflows. Automation increases analytical accuracy by minimizing opportunities for manual error, in turn improving reproducibility and protecting the integrity of analytical data. A preclinical study may involve up to 100 samples, each of which requires tedious immunoaffinity capture, digestion, sample transfer, denaturation, reduction, and subsequent manual cleanup steps. By implementing such procedures in parallel, and eliminating the need for some steps, immuno-MS can shorten the time required for this process to a matter of hours.
Through removing the need to generate specific antibodies per biotherapeutic candidate, immuno-MS enables a universal method that can be applied to, for example, all antibodies of type IgG-1 in animal serum matrices at the pre-clinical phase. With immuno-MS, drug developers can utilize antibodies that are specific enough to identify a compound from the matrix at the preclinical stage, and then later increase antibody specificity as needed. The ability to progress preclinical testing at high throughput while such antibodies are being developed is hugely valuable in keeping production moving and helps to eliminate costly bottlenecks and downtime.
Developed immuno-MS2 methods have also demonstrated the ability to monitor the structural integrity of mAbs in vivo during quantitation, a valuable benefit that enables more comprehensive knowledge of drug metabolism and behavior. Overall, immuno-MS minimizes the hurdles to biotherapeutic analysis, enables significant optimization of preclinical processes, and increases confidence when moving from preclinical to clinical testing. This essential step defines whether a therapeutic product – and, by extension, the drug developer themselves – is likely to experience success or failure.
Conclusion
Innovative methodologies are accelerating the development and bioanalysis of novel biotherapeutic drugs, and enabling organizations to more accurately assess candidate antibodies at earlier stages in the pharmaceutical pipeline.
By combining the benefits of the ‘gold standard’ immunoaffinity assays traditionally used in bioanalysis and the precise detection capabilities of MS, immuno-MS methods enable an accurate, sensitive, selective, and robust preclinical analysis of mAb drugs. Techniques based on immuno-MS are becoming increasingly popular in preclinical analysis, reflecting their ability to optimize this stage of drug development. As a result of its increased automation and fast, streamlined sample preparation protocols, immuno-MS can achieve good sensitivity, speed, and robustness. Unlike techniques based solely on immunoassays, immuno-MS can be applied to large subclasses of antibodies in all animal serum matrices without modification, removing the need to develop new antigen-specific antibodies for each individual biotherapeutic candidate at an early stage (typically done at a high cost and on long timelines).
The fast, reproducible, universal approach of automated immuno-MS optimizes the process of developing successful and effective drug products, protecting organizations from the delays, costs, and pitfalls of biotherapeutic production – and helping to make these hugely promising therapies available to the patients that need them.
References
- Pento, J.T., (2017) Monoclonal Antibodies for the Treatment of Cancer. Int J of Cancer Research and Treatment
- Tang, J., Zhang, X., Zhou, Y., Min, D. (2020) A fast and simple immuno-mass spectrometry method for preclinical bioanalysis for IgG1 mAb. App note 73684.
- Johnson, D. E. (2018) Biotherapeutics: Challenges and Opportunities for Predictive Toxicology of Monoclonal Antibodies. Int J Mol Sci. 2018 Nov; 19(11): 3685.
- Kraljevic, S., Stambrook, P. J., and Pavelic, K. (2004) Accelerating drug discovery. EMBO reports 2004 Sep; 5(9): 837–842.
Author Biography
Jon Bardsley has over a decade of experience in DMPK and regulated bioanalytical studies within large pharmaceutical environments. His passion for the development of robust and accurate analytical methods for high-throughput studies has seen him also gain experience working in contract research organizations. Jon sits on the Reid Bioanalytical committee of the Chromatography Society and is a subject matter expert in the bioanalysis community. Following a period as Senior Applications Specialist for Chromatography, Jon now holds the position of Vertical Marketing Specialist for Pharma & BioPharma within Thermo Fisher Scientific, to bring relevant technologies together to help solve customer challenges.