Contract Research Organizations & Automated Patch Clamp
Contract Research Organizations (CROs) provide outsourced research services to pharmaceutical, biotechnology, and medical device companies. CROs must maintain high levels of quality and compliance with regulatory requirements while constantly striving to increase the efficiency and turnaround of data to their customers. Highly efficient solutions are crucial to adapting to changing client needs and priorities.
Automated patch clamping provides the CROs with a powerful tool for studying ion channels and their response to drugs. The automation of the process improves laboratory efficiency, quality data, and throughput, while also providing effective client communication.
Increased laboratory efficiency
By using automated patch clamp systems, you are automating many of the time-consuming steps involved in manual patch clamp recordings. Thereby, saving significant time that staff can use for data analysis and assay optimization. Automating the process enables the CROs to test more compounds in a shorter amount of time, leading to increased efficiency in drug discovery.
High Throughput Screening (HTS)
Automated patch clamp enables the CROs to test large numbers of compounds in a short amount of time, which can help to identify potential drug candidates more quickly. This can speed up the drug development process and help their clients to get new drug discoveries and treatments to market faster.
Improved data quality & accuracy
Automated patch clamp techniques provide highly accurate and reliable data, which helps the CROs make better-informed decisions about drug development for their clients. Automating the process also eliminates the human error factor, which is associated with manual patch clamp recordings. Thereby, improving the accuracy and reliability of data.
Reduced data variability
With automated patch clamp, researchers can reduce the variability of data between different experiments, which improves the consistency and reliability of their results. This helps ensure that the data generated by different labs are more comparable, leading to better data sharing and more efficient drug discovery.