Bioinformatics-Analysis, a division of CD Genomics, provides bioinformatics services related to every stage of clinical research. You only need to provide the original data, and we will provide you with professional data analysis services. Finally, we will provide you with a one-stop data analysis service that displays the list of detected variants, as well as detailed information and visual charts. With a professional data analysis team, we provide you with customized data analysis services to meet your research needs. Totally, we take care of your bioinformatics, so you can focus on the real business.
Introduction of Preclinical Research
Preclinical research involves the drug evaluation of potential therapeutic interventions in cells and animals. Then, candidates for entry into clinical trials can be selected based on their effectiveness and safety in disease models. Before clinical trials begin, all drugs need data from various toxicological preclinical studies to support their potential safety in humans. Pharmacogenomics is an emerging discipline based on molecular pharmacology and functional genomics developed in the late 1990s. Through the analysis of the genome, we can study the related genes that lead to differences in the metabolism of drugs in the body and the different responses of different genotypes to drugs. Thereby accelerating the evaluation of drug effects and safety. It is an important method to study the rational use of medicines and personalized medicines.
Although genomics methods are often used in the target identification/verification phase of drug development, genomics methods are often ignored in this preclinical stage. Before the drug enters the clinic, it is necessary to conduct efficacy and safety tests in vivo and in vitro, and this process is time-consuming and expensive. Moreover, the results of the efficacy and safety evaluation data obtained are not representative of all individuals. Through genomics methods, microarray technology or next-generation sequencing technology, combined with bioinformatics methods, it is possible to efficiently identify genomic changes related to toxicology or non-targeting effects.
Fig 1. Genes involved in warfarin metabolism and mechanism of action. (Kaye JB, et al. 2017)
Bioinformatics in Preclinical Research
Through the analysis of microarray data and the data obtained by sequencing technology, the information of genomic variation can be mined. Combined with related drug databases, predict the efficacy of drugs, predict the dose of drugs, avoid ADR of drugs, and find new targets for drugs. It is also possible to search for genetic polymorphisms related to individual differences in drug response, including: drug metabolizing enzyme gene polymorphisms, drug transport gene polymorphisms and drug action target gene polymorphisms. You only need to mention the raw data, we will analyze and visualize the data through software and machine learning algorithms.
Fig 2. CD Genomics bioinformatics data analysis process.
What can CD Genomics Do?
We can assist in your clinical research at every stage by offering our proprietary bioinformatics analysis approaches. Such as microarray data analysis and genomic data analysis. In pre-clinical research, we can identify genomic changes associated with toxicology and/or off-target effects.
Through the analysis of gene polymorphisms related to drug metabolizing enzymes, predict the reasons for individual differences in drug reactions.
Analyze the gene polymorphisms of drug transporters to predict the reasons that affect the drug transport, absorption, distribution and elimination of differences in the body.
Analysis of gene polymorphisms of drug targets can predict the causes of different drug effects (such as different dosages) in individuals.
CD Genomics has rich data analysis experience in preclinical data research, such as genomics-related data analysis of warfarin, losartan, irbesartan and other drugs. With years of data analysis experience, we will provide you with a satisfactory analysis result report. For preclinical research data analysis, if you have any questions, please feel free to contact us for details.
Reference
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Kaye JB, et al. Warfarin Pharmacogenomics in Diverse Populations. Pharmacotherapy. 2017 Sep;37(9):1150-1163. doi: 10.1002/phar.1982. Epub 2017 Sep 6. PMID: 28672100; PMCID: PMC6913521.
