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Improving efficiency in drug discovery and development

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  • Find solutions to reduce risk in your workflow
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      • Matched antibody pairs
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                      • Recombinant antibodies

                        Highlighting the crucial role of high-quality validated biological reagents and tools with a secure long-term supply. 

                        Published November 23, 2021

                        Download the PDF version of this page to view it at any time.

                        Download the PDF

                        Contents

                        • Introduction
                        • Recombinant monoclonal antibodies – enabling scale-up with a guaranteed long-term, consistent supply to deliver reproducible results
                        • Matched recombinant antibody pairs – supporting reliable results and scale-up of ELISA assays
                        • Directly conjugated primary antibodies – streamlining your workflow while saving hands-on time
                        • High-throughput multiplex immunoassay – accelerating next discovery by gathering more meaningful data
                        • High-quality recombinant proteins validated to meet stringent specifications  – driving consistent long-term performance across assays and cell cultures
                        • CRISPR cell line engineering services – efficiently creating improved disease models to predict drug safety and efficacy more accurately
                        • Conclusion
                        • References

                        Introduction 

                        Biopharma companies continue to confront productivity challenges with creating a new drug and bringing it to the market, including increasing pressure to progress their therapeutic assets through the drug development process more quickly1,2. While the drug development process becomes lengthier and more expensive3–5 (Figure 1), the rate of new therapeutic agent approvals has remained stable.

                        Figure 1. Bringing a new drug to market cost USD 2.17 billion in 2018 compared to USD 1.18 billion in 2010, a near 100% increase3. As well as costing more, drug development has become a lengthier process, requiring on average 10-15 years during the past two decades versus 9.7 years in the 1990s4,5.

                        Factors contributing towards increased development time and expenditure include more stringent regulatory requirements, struggles with recruiting clinical trial patients, and the industry’s drive towards high-risk, high-reward research areas such as oncology5. Another major contributor is Avoidable Experiment Expenditure (AEE), defined as “all inefficiencies and productivity challenges in designing and carrying out preclinical experiments”6.

                        Preclinical research and development, which accounts for ~42.9% of the overall spend on drug development, still relies heavily on experiments using critical biological reagents. Alarmingly, irreproducibility rates in preclinical experiments can exceed 50%, costing the industry nearly $48 billion annually7. While several factors account for AEE, inappropriate or faulty reagents are one of the most significant contributors such that over USD 17 billion can be assigned to poor quality biological products and reference materials. This is also the cause for over 36% of preclinical R&D experiments being unproductive6,7.

                        Reducing biological reagent-related AEE could lead to organizations collectively reclaiming ~US$17 billion in unnecessary spending while streamlining workflows and improving R&D efficiency. In addition, candidate drugs could progress to clinical trials faster, potentially accelerating their progress through the development pipeline.

                        Unlike with the clinical phases of drug development, no regulatory authorities, such as the FDA or EMA, regulate the standards around how biological reagents are developed or used. Therefore, commonly used biological reagents – including antibodies, recombinant proteins, cell lines and associated model systems – can have variable performances depending on the biological systems in which they are both created and employed8,9.

                        Using well-validated commercially available biological reagents saves valuable time and money, increasing the efficiency of drug discovery and development applications across workflows. Here, we discuss a wide range of consistent, high-quality products that can help overcome inefficiency challenges by enabling reproducible experiments, streamlining workflows, accelerating progress, and reducing wasted resources.

                        Recombinant monoclonal antibodies – enabling scale-up with a guaranteed long-term, consistent supply to deliver reproducible results

                        Using poor-quality antibodies for preclinical studies or biomarker detection can damage and invalidate these studies and subsequent costly clinical trials9. To deliver reproducible results throughout the lengthy drug development process, scientists need well-characterized, specific antibodies that perform consistently across all applications and workflows.

                        Monoclonal antibodies are invaluable tools for effective drug or biomarker discovery and development, used to quantify, localize, and modulate proteins of interest. However, conventional hybridoma-produced monoclonal antibodies can exhibit issues with specificity and reproducibility. The specificity issues arise from the hybridoma cell line expressing additional productive heavy or light chains, rendering the antibodies non-specific. Also, over time, hybridoma cell lines can experience gene loss or mutations and genetic drift, resulting in variations to the antibodies produced.

                        Recombinant monoclonal antibodies can help overcome specificity and reproducibility issues experienced with hybridoma-derived monoclonal antibodies10. Recombinant manufacture occurs in vitro by cloning antibody genes into high-yield expression vectors, which are then introduced into expression hosts to generate recombinant antibodies. Since the recombinant antibody’s gene sequence is known, they can be further developed using antibody engineering techniques at the genetic level to enhance an antibody’s performance, such as improving affinity or reducing background or non-specific signals to maximize sensitivity.

                        Unlike the hybridoma antibody production, recombinant expression of antibodies is controlled and reliable. Therefore, recombinant antibodies can be readily scaled-up, demonstrating outstanding batch-to-batch consistency and guaranteeing the security of a long-term supply. This makes recombinant antibodies an excellent solution when using the same antibody for long-term studies or across multiple samples, ensuring highly reproducible results required for drug discovery and development research.

                        Figure 2. Summary of recombinant antibody features.

                        Leading experts in the antibody field, including Dr Andrew Bradbury, CSO at Specifica and founding President of the Antibody Society, are advocating strongly for the use of recombinant antibodies in research to improve reproducibility: “If all antibodies were defined by their sequences and made recombinantly, researchers worldwide would be able to use the same binding reagents under the same conditions11.”

                        For all antibodies, irrespective of their production method, it is essential to assure the highest quality by validating each batch of an antibody extensively for specificity and selectivity, including appropriate application-specific validation. One of the most accepted and trusted approaches to validate antibody specificity is knock-out (KO) validation. This stringent approach involves testing each batch of antibodies with CRISPR-gene edited KO cell lines, which do not express the target protein, versus the wild-type cell line.

                        Matched recombinant antibody pairs – supporting reliable results and scale-up of ELISA assays

                        Securing a consistent supply of highly specific recombinant monoclonal antibodies is critical to developing robust and reliable assays that use multiple samples for long-term drug development studies. Developing a sandwich ELISA requires careful selection of a matched antibody pair, ie an unlabeled capture antibody and a conjugated detector antibody that both bind specifically to the target protein, as well as the inclusion of a calibrated recombinant protein standard for quantification.

                        Using optimized recombinant monoclonal antibody pairs (Figure 3) can help avert the reproducibility and scalability challenges previously faced by researchers using monoclonal (hybridoma) or polyclonal antibodies, which can cause variability in results. Screening and optimizing the antibodies as a pair is crucial for their validation. The pairs are screened for sensitive performance and rigorously tested in various complex sample types, including plasma, serum, and cell lysates. Recombinant antibody pairs facilitate cost-effective drug discovery by enabling efficient scale-up from small pilot studies to large throughput assay platforms.

                        Directly conjugated primary antibodies ­– streamlining your workflow while saving hands-on time

                        As the complexity of studies and assays increases, incorporating conjugated primary antibodies in such applications as IHC and flow cytometry allows for fewer incubation steps and less liquid handling, thereby saving hands-on time and streamlining the workflow. Also, compared to secondary antibodies, directly conjugated primary antibodies can reduce non-specific binding and minimize species cross-reactivity.

                        However, finding the right combination of antibody and label of interest remains a key challenge with directly conjugated antibodies. If a suitable conjugated antibody is not available commercially, using fast and simple antibody conjugation kits can be a straightforward solution. It’s crucial to choose kits with high batch-to-batch consistency, producing reproducible results at various conjugation scale. Alternatively, partnering with a supplier with conjugation expertise, who can create custom antibody conjugation solutions, will minimize the trial and error inherent to the conjugation process, saving valuable resources and time.

                        One often overlooked consideration is whether primary antibodies or antibody pairs are formulated with BSA or other additives such as glycerol or sodium azide, which can interfere with the conjugation reaction and final product. Also, for functional assays relying on cell culture, antibody formulations should not include azide, which is toxic to the cells. So, to enable efficient antibody labeling and functional assay applications, antibodies and antibody pairs should also be formulated in azide-free and BSA carrier-free buffers.

                        High-throughput multiplex immunoassay – accelerating next discovery by gathering more meaningful data

                        High-throughput screening (HTS) is a key process routinely used during early drug discovery to narrow down huge compound libraries to find those that modulate the activity of a biological target. HTS requires scalable, high-quality immunoassays to identify the most promising compounds quickly, efficiently, and with minimal costs12.

                        Traditional single-analyte immunoassays, such as ELISA, are still invaluable in early discovery and for measuring therapeutic responses in clinical trials. However, they are inefficient in terms of cost, labor, time, and sample volume required when measuring more than one target protein in HTS. Multiplex immunoassays address those challenges by studying several targets in a single well using minimal amounts of sample, exponentially increasing the number of data points collected in HTS. By measuring multiple analytes simultaneously, multiplex immunoassays provide researchers with greater insight from a single assay. They can accelerate and scale up biomarker profiling while minimizing a researcher’s workload.

                        High-throughput multiplex immunoassays combine multiplexing with high-throughput capabilities, thus enabling more insightful data to be harvested, improving decision-making at the early stages of drug discovery without sacrificing assay performance or data quality. There are several factors to consider when choosing a suitable multiplex assay, such as assay specificity, sensitivity, and reproducibility (which all depend on high-quality antibody pairs), automation compatibility, and no-wash vs wash format (Figure 4). Automation reduces potential errors while enabling the scale-up process. A no-wash assay workflow decreases the number of steps between reagent handling and final data collection, increasing throughput.

                        Figure 4. The main factors to consider when choosing a multiplex assay for use in drug discovery. 

                        High-quality recombinant proteins validated to meet stringent specifications – driving consistent long-term performance across assays and cell cultures

                        Since proteins are the targets for most marketed drugs, high-quality purified recombinant proteins are required for in vitro and in vivo assay development, compound screening, and structural studies. Recombinant proteins require strict quality controls since protein quality issues affect the reliability of their intended applications. From basic to translational research and clinical applications, cell culture is an essential technique that requires bioactive proteins such as cytokines and growth factors. Since the quality of the proteins can significantly influence the properties and function of cultured cells, these bioactive proteins must be produced to the highest standard to ensure reproducible and reliable results13.

                        To support optimal bioactivity, recombinant bioactive proteins are expressed in mammalian systems to have the correct folding and posttranslational modifications (Figure 5). Each new batch of a bioactive protein must pass stringent quality control specification tests to ensure consistent integrity, purity, concentration, and correct folding, as well as confirm biological activity in a well-defined product-specific in vitro functional assay. Each new batch has to be verified against data for a master lot to control for assay variability. 

                        Figure 5. Key characteristics of Abcam premium grade bioactive proteins.

                        CRISPR cell line engineering services – efficiently creating improved disease models to predict drug safety and efficacy more accurately

                        Approximately 95% of drugs that enter clinical trials are unsuccessful. One of the major causes of failure at this phase of drug development is the lack of efficacy for the intended disease indication14. This lack of efficacy is attributed to the poor validity and predictability of in vitro and in vivo preclinical human disease models, leading to a high false discovery rate in preclinical studies. Many of the current preclinical assays lack suitability in addressing safety issues and evaluating off-target effects.

                        CRISPR gene-editing has brought increased accuracy and speed to cell engineering, transforming the development of more complex disease-relevant cell-based assays to improve predictability for drug therapies15-19. CRISPR is now being employed at each preclinical stage to speed workflows and accelerate and validate therapeutic assets in the pipeline, aiming to decrease later stage attrition and, ultimately, reduce development costs.

                        CRISPR is better at knocking out the targeted gene more fully than other techniques, such as RNAi, and avoiding unwanted effects, making large-scale gene-function experiments much more reliable. Likewise, CRISPR KO cell lines are one of the most valuable tools for validating an antibody’s specificity.

                        Despite the promise and possibilities CRISPR has brought to drug discovery and development, the engineering of stable CRISPR cell lines or models can be complex and time-consuming. Rather than spending months creating your own CRISPR knock-out cell lines (Figure 6), remove technical and time constraints from your projects by choosing from a wide range of commercially available, physiologically relevant cell lines or partnering with companies with gene-editing expertise who can offer custom engineered cell lines. 

                        Figure 6. The comparison of timelines for in-house designed vs commercially available CRISPR KO cell lines.

                        Conclusion

                        Partnering with a reputable supplier of high-quality, well-validated biological reagents early in the drug discovery process offers a viable solution to overcoming inefficiency challenges and saving valuable time and resources. Since drug development is a long process, many studies demand a long-term supply of batch-to-batch consistent and comprehensively validated biological reagents. This article reviewed various product solutions that can ensure reproducible results across the whole drug development pipeline while streamlining the processes, accelerating progress, and reducing wasted resources.

                        Firstly, recombinantly produced antibodies and proteins are inherently suitable for controlled protein expression and generating consistent products. Recombinant production can be easily scaled-up to guarantee a long-term supply of required protein or antibody and deliver reproducible results across the whole drug development process.

                        Secondly, using automatable multiplex assays instead of singleplex assays or replacing secondary antibodies with primary conjugated antibodies can decrease the number of process steps and liquid handling, thus streamlining workflows and reducing wasted resources. Finally, expertly engineered CRISPR cell lines help create improved disease models to predict drug safety and efficacy more accurately while accelerating the speed of the preclinical pipeline.

                        References:

                        1. Paul, S., Mytelka, D., Dunwiddie, C. et al. How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nat Rev Drug Discov 9, 203–214 (2010).
                        2. Pammolli, F., Magazzini, L. & Riccaboni, M. The productivity crisis in pharmaceutical R&D. Nat Rev Drug Discov 10, 428–438 (2011).
                        3. Terry, C., Lesser, N. Ten years on, Measuring the return from pharmaceutical innovation 2019. Deloitte. https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-ten-years-on-measuring-return-on-pharma-innovation-report-2019.pdf. Accessed September 2021. (2019).
                        4. DiMasi, Joseph A., Henry G. Grabowski, and Ronald W. Hansen. Innovation in the Pharmaceutical Industry: New Estimates of R&D Costs. Journal of Health Economics. North-Holland, February 12, (2016).
                        5. Norman, Gail A. Van. Drugs, Devices, and the FDA: Part 1: An Overview of Approval Processes for Drugs. JACC: Basic to Translational Science. Elsevier, April 25, (2016).
                        6. BenchSci: Avoidable Experiment Expenditure (AEE) Whitepaper. https://landing.benchsci.com/avoidable-experiment-expenditure#form. Accessed August 2021. (2020).
                        7. Freedman LP, Cockburn IM, Simcoe TS. The Economics of Reproducibility in Preclinical Research [published correction appears in PLoS Biol. 2018 Apr 10;16(4):e1002626]. PLoS Biol. 13(6):e1002165. (2015).
                        8. Depalmo, A. Authenticating biological reagents. Lab Manager. https://www.labmanager.com/business-management/authenticating-biological-reagents-2435. Accessed August 2021. (2018).
                        9. Baker, M. Reproducibility crisis: Blame it on the antibodies. Nature 521, 274–276 (2015).
                        10. Marx, V. Change-makers bring on recombinant antibodies. Nat Methods 17, 763–766 (2020).
                        11. Bradbury, A., Plückthun, A. Reproducibility: Standardize antibodies used in research. Nature 518, 27–29 (2015).
                        12. Eller, C. How to accelerate drug discovery with optimized high-throughput screening. Select Science. https://www.selectscience.net/editorial-articles/how-to-accelerate-drug-discovery-with-optimized-high-throughput-screening/?artID=55256&utm_source=Abcam&utm_medium=referral&utm_campaign=social-sharing-cc1. Accessed September 2021. (2021).
                        13. Gerhartz, B. Excellent standards drive commercial demand in bioproduction. Laboratory News. https://www.labnews.co.uk/article/2031177/excellent-standards-drive-commercial-demand-in-bioproduction. Accessed October 2021. (2021).
                        14. Hingorani, A.D., Kuan, V., Finan, C. et al. Improving the odds of drug development success through human genomics: modelling study. Sci Rep 9, 18911 (2019).
                        15. Corrigan-Curay J. et al. Genome Editing Technologies: Defining a Path to Clinic. Mol Ther. 23(5): 796–806 (2015).
                        16. Muthuirulan, P. CRISPR: Kick-starting the revolution in drug discovery. Drug Target Review. https://www.drugtargetreview.com/article/53152/crispr-kick-starting-the-revolution-in-drug-discovery/ . Accessed October 2019. (2019).
                        17. Enzmann, B.L, Wronski, A. How CRISPR is accelerating drug discovery. GENENG News. https://www.genengnews.com/insights/how-crispr-is-accelerating-drug-discovery/. Accessed September 2021. (2019).
                        18. Carter, C. SelectScience. Speeding the transition from bench to bedside with CRISPR-Cas9. 223 Jul. https://www.selectscience.net/editorial-articles/speeding-the-transition-from-bench-to-bedside-with-crispr+cas9/?artID=52023. Accessed August 2021. (2020).
                        19. Scott, A. A CRISPR path to drug discovery; Gene editing is quietly revolutionizing the search for new drugs. Nature 555, 10-11 (2018). 



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