Over the past two decades, pharmaceutical companies have expanded their focus in new drug development efforts beyond small molecules to include large molecules or biopharmaceuticals. In a September 2016 publication by EvaluatePharma 1, they estimated by 2022, biologic drugs will contribute 50 per cent of the top 100 pharmaceutical product sales. Biopharmaceuticals have been called the most sophisticated and elegant achievements of modern science (Otto et al, 20142). They are complex macromolecules with intricate three dimensional structures that are often isolated from living sources. Primarily composed of amino acids or nucleic acids, biopharmaceuticals often have modifications such as sugar moieties that are critical for proper function.
One area of intense focus is the development of biologic drugs that combine the specificity of large molecules and the potency of small molecules. These biologic drugs perform their jobs remarkably well and offer high efficacy with few side effects (Sekhon et al, 20103). With this new sophistication and enhanced performance comes added complexity in development and manufacturing. Therefore, a tremendous number of potential bio therapeutic proteins need to be rapidly and accurately characterized, so that data driven decisions can be made that move the best candidates through the drug discovery and development process.
The characterization and analysis of protein biotherapies requires robust and highly reproducible sample preparation techniques. For purposes of this article, sample preparation will be defined as the preparation of proteins from complex biological matrices for analysis using liquid chromatography with detection by mass spectrometry (LC-MS), tandem mass spectrometry (MS-MS), conventional detectors, or a combination of these.
Today’s analytical instrumentation offers performance advantages in terms of specificity, acquisition rate, and sensitivity. Scientist are now able to acquire reproducible, accurate data faster than ever before. Instrumental analysis is no longer the bottleneck in reporting a sample. The time needed for sample preparation and data analysis are often the largest contributor to the overall time and effort it takes to complete sample analysis.
In the analysis of protein therapeutics, there are many approaches to sample preparation. Three common techniques that are often used in the biopharmaceutical lab either alone or in combination are: affinity purification, in-solution digestion and peptide cleanup.
Affinity purification is a method of separating biochemical mixtures based on a highly specific interaction such as that between antigen and antibody, enzyme and substrate, or receptor and ligand. Typical steps involved are purification and concentration of a substance from a mixture, such as cell culture supernatants, cell lysates, and serum into a buffering solution (Morris et al, 20144).
In-solution digestion is another common method of preparing protein samples for detailed analytical characterization. Proteins in-solution are usually denatured by using chaotropic agents or detergents. During this step, the disulfide bonds must also be reduced, and the sulfhydryl groups must be alkylated to prevent the disulfides from re-forming. Before adding protease, usually trypsin, the denaturants must be either diluted or removed so the denaturing reagents do not interfere with subsequent enzymatic digestion. The protein samples are then incubated with protease for several hours before the resulting peptides can be analyzed by MS (Medzihradszky, 20055).
Peptide analysis can present a number of issues that affect detector response, due to the presence of unwanted interferences from either the matrix or from reagents and other additives used to facilitate protein digestion. Peptide cleanup techniques employed to remove these interferences are required to be quick, effective and simple. Because of the effectiveness at sample cleanup, ease of use, and ability to have a generic methodology solid-phase extraction (SPE) is commonly employed to remove unwanted reagents and particulates from the digested sample prior to MS analysis (Henion, 19996). This method typically provides a high recovery of the peptides and can be highly reproducible. Reproducibility is important as this enables users to confidently assign data differences to the sample and not the methodological conditions used. An additional concentration step such as dry down may also be necessary before analysis.
Historically the bulk of work done to prepare protein samples for analysis has been performed by LC-MS or LC-MS/MS analysis, manually on a relatively small number of samples. These sample preparation steps consist of a series of complex, time-consuming, and potentially error-prone tasks that can lead to operator fatigue due to repetitive movement. Due to improved technology and lower costs, laboratories now have the option of transitioning to automated sample preparation. Automation provides improved consistency, reduction in human error, scalability, and reduction in labor costs.
Agilent Technologies has created a cartridge-based system, the Agilent AssayMAP Bravo platform, that automates a wide variety of LC/MS sample prep workflows such as affinity purification, in-solution digestion, peptide cleanup, phosphopeptide enrichment, and N-glycan preparation, on a single, easy to use instrument that can meet the increasing requirements for high-throughput, robust, and reproducible sample preparation (Russell et al, 20177). The liquid handling of the AssayMAP Bravo provides precise flow control through 8 to 96 microchromatrography cartridges allowing sample preparation to be performed in a highly parallel format that enables high reproducibility, reduced hands on time, excellent sample recovery, efficient washing, and very low elution volumes.
To manage the transition from manual to automated sample preparation, a laboratory should be clear about its specific needs. Space requirements, the type of automation required, and the level of automation expertise required in the lab should all be considerations. Available space is also an important consideration as there are a very wide range of options from compact to very large systems. A compact system is ideal for laboratories with bench space restrictions and/or tight budgets. It provides the benefit of reduced hands on time by automating the most tedious liquid handling steps. A compact system may however, require frequent walk-ups so that operators can change tips boxes or introduce reagents.
Scientists should also consider the type of work that needs to be done. Deciding if the instrument will be a dedicated, single-purpose instrument, or a system capable of adapting to different processes will be key to selection. Determining what sample prep should be automated and whether to take an online or offline approach is also central to successfully automating sample preparation. Sample preparation methods that require high-throughput, reproducibility and robustness, will benefit greatly from automation.
Finally, a lab should also consider how much programming they are willing to learn. In the past, one of the challenges of implementing automation in a biopharma lab was the requirement for a specialized robotics expert to program the instrumentation to perform routine tasks. There are varying levels in complexity of software offered by automation providers. If ease-of-use is a priority, selection of an automation platform with user-friendly software and flexibility would be a preference. The most straightforward way to automate a sample preparation protocol is to work with a vendor that has pre-programmed methods for the type of analysis that a lab requires. There are a variety of automation choices available in the market today that increase throughput, provide consistency in results, streamline workflows, and potentially provide walkaway time to researchers so that they can perform other tasks.
By automating sample preparation, biopharma laboratories can rapidly and accurately characterize more bio therapeutic proteins that could eventually benefit more patients and improve overall health outcomes. Automation increases throughput, boosts productivity and reduces variability so that data driven decisions about the best possible therapies can be made more quickly.
1. EvaluatePharma® World Preview 2016, Outlook to 2022 9th Edition– September 2016
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4. Morris, John, M Knudsen, Giselle, Verschuerer, Erik, Johnson, Jeffrey, Cimermancic, Peter, Greninger, Alexander, Pico, Alexander. Affinity purification–mass spectrometry and network analysis to understand protein-protein interactions. Nature Protocols Volume: 9, Pages: 2539– 2554.201
5. Medzihradsky, Katalin. Mass Spectrometry: Modified Proteins and Glycoconjugates In-Solution Digestion of Proteins for Mass Spectrometry. Methods in Enzymology. Volume 405, 2005, Pages 50–65
6. Hennion, Marie-Claire, Solidphase extraction: method development, sorbents, and coupling with liquid chromatography. Journal of Chromatography. Volume 856, Issues 1–2, 24 September 1999, Pages 3–54
7. Jason D. Russell, Zachary Van Den Heuvel, Michael Bovee, Steve Murphy. Workflow Automation for LC/MS: In‑Solution Protein Digestion, Peptide Cleanup, and Strong Cation-Exchange Fractionation of Peptides Enabled by AssayMAP Technology. Agilent Technologies, Inc., 2013.
About the Authors:
Lisa Sapp is the Biopharma Market Manager for Agilent Technologies, Inc.
Steve Murphy, Ph.D., Director of Development-BioPharma Solutions and AssayMAP, Agilent Technologies, Inc.