We all know drug development is a long, arduous, and very expensive process. One of the biggest challenges faced along the way is the need to uncover meaningful insights from vast amounts of data gathered during efficacy and toxicity testing. Bioanalysis requires complex evaluation of data collected over time, examining how compounds react with living things.

These studies are essential to ensure that new drugs are effective and safe. They take months or even years to complete, are very complex, and are a major source of stress for scientists and other lab researchers. In addition to screening hundreds of possible drugs simultaneously, management frequently pressures them to evaluate and select the best compounds as quickly as possible.

The key to achieving these goals is to establish testing protocols and measurement systems that are as standardized and consistent as possible. With the right tools, clinical pharmacology researchers can work more efficiently, make informed decisions faster, and integrate processes. All of this reduces the amount of lab time required to perform analysisincreases accuracy, and improves screening time. The end result is reduced cost and time to screen out suboptimal or dangerous drugs.

The role of bioanalysis

Bioanalytical testing involves quantitatively measuring drugs and how they metabolize in biological fluids, such as blood, plasma, urine, or tissue samples. It seeks to determine two properties of a drug candidate:

  • Pharmacokinetic (PK) — how a drug is absorbed, distributed, metabolized, and eliminated by the body
  • Pharmacodynamic (PD) — how the drug interacts with its target receptor or enzyme to produce a therapeutic effect

Bioanalytical testing is typically performed using analytical techniques such as liquid chromatography (LC), gas chromatography (GC), mass spectrometry (MS), and immunoassays. These techniques are highly sensitive, specific, and accurate and allow for the quantification of drugs and their metabolites at very low concentrations.

Another important parameter in this process is the “cut point” or lower limit of quantification (LLOQ), which is the lowest concentration of a substance that can be accurately and reliably quantified using a given bioanalytical method. This matters because it determines the sensitivity and accuracy of the testing method. A low LLOQ enables easier validation, while a high value may result in inaccurate or imprecise measurements.

Bioanalytical data matters at every stage of drug development

Although bioanalytical testing plays a critical role in the clinical development phase, it’s important throughout the entire drug development process.

During clinical development, bioanalysis is used to measure the concentration of the drug and its effects in biological samples obtained from study participants. This information is then used to evaluate the drug’s PK properties and to determine the appropriate dosing regimen.

Testing is also used to assess the drug’s efficacy and safety by measuring the concentration of the drug and its metabolites in relation to the therapeutic and toxic effects observed in study participants. This information is used to determine the drug’s therapeutic window and to establish safe and effective dosing regimens.

In addition, regulatory agencies worldwide, such as the US Food and Drug Administration (FDA), require bioanalytical testing to demonstrate a drug candidate’s safety and efficacy before it can be approved for clinical use. Therefore, the quality, sensitivity, and accuracy of the bioanalytical methods used to measure drug concentrations are critical to the success of the clinical development program and the ultimate approval of the drug.

Maximizing the efficiency of screening practices

According to a report by the Tufts Center for the Study of Drug Development, the estimated cost of developing a new drug from discovery to approval is approximately $2.6 billion. Early-stage detection of drug failures is an absolute must in order to reduce lost time and revenue.

The necessary computation and analyses require heavy usage of statistical computational techniques on the sample data residing in the laboratory information management systems (LIMS). In most cases, there is little or no integration between the LIMS software and the analytical tools used for such computations. This makes retrieval of the relevant data from the LIMS and the subsequent postback of the computed analyses to the LIMS a cumbersome and inefficient process.

Furthermore, most available computational tools are fairly rudimentary and don’t offer the range of statistical capabilities required in various stages of research and development.

These challenges can be overcome with the LabVantage Analytics (LVA) Clinical Pharmacology Modeling Solution. LabVantage has joined with TCG Digital’s mcube to provide a seamlessly integrated and natively supported business intelligence and point solution application. It can be triggered and manipulated from directly within the LIMS application and uses information captured by the LIMS.

LVA Clinical Pharmacology Modeling Solution includes PK/PD modelers, immunogenicity cut point analyzers and a library of pre-built calibration curves commonly used in bioanalysis. This enables lab researchers to quickly and easily compare their own data to the reference curves in the library, allowing for rapid and accurate quantification of drug concentrations or effects.

In PK analysis, calibration curve libraries are used to measure the concentration of a drug in biological samples, such as blood or urine, at various time points after drug administration. These measurements can be used to determine important PK parameters such as clearance, volume of distribution, and half-life.

In PD analysis, calibration curve libraries are used to quantify the effect of a drug on a biological system, such as the inhibition of an enzyme or the reduction of tumor size. By comparing the drug effect in a sample to the reference curves in the library, researchers can determine the concentration of drug required to achieve a particular effect.

The benefits of this approach include:

  • A dramatic reduction in computational errors, enabled by template-driven utilities
  • Major improvements in turnaround time due to faster processing
  • Greater computation accuracy and precision stemming from access to a huge number of computational algorithms
  • Increase in lab efficiency and throughput
  • Benchmarking across multiple labs to maximize ROI
  • Reduced cost associated with poor quality
  • Standard reports and dashboards out of the box

The LabVantage Analytics Clinical Pharmacology Modeling Solution is designed to provide a complete solution that integrates seamlessly with LabVantage LIMS. For more details, contact us today.