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• W2040372209 abstract "A constant demand in the pharmaceutical industry is to accomplish more with the same or fewer resources. It is generally accepted that a major expense of an established laboratory is the personnel, which constitutes a fixed cost. Improving the efficiency of laboratory personnel through automation reduces the overall cost.In addition to this demand, there is an expectation for the production of high-quality data with an ever-shortening turn-around time. To meet this challenge, a significant amount of pressure is brought on the analyst who must find ways to increase the efficiency and throughput with limited resources.Large molecule bioanalysis presents unique challenges, compared to small molecule analysis, that add to the complexity of quality data generation. Firstly, the number of samples to be analyzed may be doubled or tripled when compared to bioanalysis for small molecules. For example, unlike small molecules, monoclonal antibodies typically have long half-lives necessitating the collection of many sampling time points. In addition to the bioanalysis of the therapeutic compound for pharmacokinetic purposes, these macromolecules may elicit anti-drug antibodies that have to be quantified in addition to the drug concentrations. Samples that screen positive for anti-drug antibodies using an antibody assay undergo secondary testing for confirmation and further characterization.The second challenge in large molecule bioanalysis is due to the limited dynamic range of the calibration curves in ligand binding assays used to estimate therapeutic drug concentrations. Calibration curves for large molecules typically range from picograms per milliliter to nanograms per milliliter whereas the serum or plasma drug concentrations are often in the micrograms per milliliter to milligrams per milliliter range. This might influence the choice of assay platform. Thus, in order for samples to be quantified by the calibration curve, they have to be precisely diluted sometimes by a millionfold in a sequence of serial dilution steps.The third challenge is the format of these assays. The 96-well plate format is commonly used, although 384 and higher well plates have been developed for a few bioanalytical assays. Because samples are run in replicate, typically fewer than 30 samples/plate (60 wells) can fit into a batch of a 96-well plate run; the remainder of the wells are taken up by the replicate calibration curve and quality control samples which are incorporated onto each plate. Execution of a manual assay may take 4 to 6 hours. Data reduction, data checking (QC), and reporting may take an additional 1 or 2 days. About 120 samples (four plates) can be processed per day by a well-trained analyst. Thus it will take 15 working days (3 weeks) to complete analysis of an 1,800-sample study. This timeframe is only applicable if samples are all available on site at the commencement of analysis. For most studies, the samples do not arrive all at once thereby reducing the assay throughput. The daily manual pipetting has been linked to repetitive stress syndrome culminating in ergonomic injuries and loss of work days. In addition, the manual mundane tasks cause worker fatigue that leads to operator errors. Thus, there is a critical need to adopt processes that will increase efficiency, quality, and reproducibility through laboratory automation.Individual biopharmaceutical companies have implemented automation in their bioanalytical laboratories (1). Others eschew automation due to cost, complexity, and compliance risk. However, to a large extent, the pharmaceutical industry and its supporting contract research organization companies have not yet successfully implemented highly automated systems for bioanalysis in a standardized way. One reason for this lack of standardization is the speed at which technology evolves, compared to the speed of technology integration in regulated bioanalytical laboratories. Other reasons range from the failure to explicitly delineate the best approaches for laboratory automation to the equipment vendors and the end users, and the lack of cooperation between vendors to manufacture laboratory equipment that can be interchanged in a “plug-and-play” manner.There are many examples of competitive companies collaborating in other highly complex and technical industries. One example is the Universal Serial Bus (USB) specification (2,3) which allows external devices such as computer mouse devices, printers, external hard drives, and digital cameras to be easily and readily plugged into computers with “plug-and-play” simplicity. A second example is the standardized 96-well plate that was initiated by the Society for Biomolecular Sciences (SBS) and published by the American National Standards Institute on behalf of the SBS (4). The definition of a microtiter plate governs various characteristics of microplates including well dimensions and plate properties. This article describes the processes most generally used in the automation of ligand binding assays (LBAs), highlights the shortcomings of current laboratory automation technologies and advocates for a common set of hardware and software standards and inter-device communications that can be used to automate sample processing." @default.
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• W2040372209 date "2012-02-01" @default.
• W2040372209 modified "2023-10-18" @default.
• W2040372209 title "Ligand Binding Assays in the 21st Century Laboratory: Automation" @default.
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• W2040372209 doi "https://doi.org/10.1208/s12248-012-9323-z" @default.
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