Bioinformatics Analysis for Drug Discovery and Development

Bioinformatics Analysis for Drug Discovery and Development

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Bioinformatics-Analysis, a division of CD Genomics, provides bioinformatics services related to drug discovery and development. We provide customers with Chip data analysis, genome data analysis, RNA data analysis and proteomics data analysis services. Identify genomic features related to drugs and compare them with genomic features of diseases through bioinformatics methods, you are now able to generate a new list of potential indications without the cost and time implications of pre-clinical or clinical studies. With a professional data analysis team, we will provide you with fast and accurate biological data analysis services.

Introduction of Drug Discovery and Development

Drug discovery and development pipelines are long, complex and depend on numerous factors. With the development of molecular biology and molecular genetics, it has been discovered that many genes are involved in the metabolism of drugs in the body, and gene polymorphisms lead to the peptide line of drug response. Therefore, pharmacogenomics (PGx) was born and began to study the individual differences in drug response from the genome level. Pharmacogenomics is the branch of genetics concerned with the way in which an individual's genetic attributes affect the likely response to therapeutic drugs.

Bioinformatics (including some artificial intelligence methods) is mainly used for data mining and discovery of new knowledge in the field of life medicine. It assists drug research through gene chip analysis, DNA sequence comparison, biological literature mining and biological data visualization. By studying the relationship between the genetic differences of different individuals and the efficacy of drugs, we can understand polymorphic genes that have important functional significance and affect drug absorption, transport, metabolism, and excretion. In order to clarify the molecular mechanism of pharmacological action and the genetic mechanism of various diseases, and ultimately guide the development of new drugs and the rational clinical use of drugs.

Fig 2. Machine learning applications in the drug discovery pipeline and their required data characteristics. Fig 1. Machine learning applications in the drug discovery pipeline and their required data characteristics. (Seung H C, et al. 2018)

Bioinformatics in Drug Discovery and Development

Bioinformatics analysis maximises the value of the drug pipeline in terms of time and costs. The application of bioinformatics in drug discovery mainly includes the following aspects:

Through gene structure and the targets of traditional drug targets in various databases (such as PharmGKB), discover new drug targets, and combine various algorithms to perform high-throughput screening of new drugs.

Carry out gene polymorphism and expression profile analysis, explore the influence of gene polymorphism on drug sensitivity, and provide a basis for personalized medicine.

By predicting the spatial structure of the protein, discovering the spatial structure of the protein related to the disease, looking for new drug targets.

Analyze the function of differentially expressed genes and discover the mechanism of pharmacological action.

Fig 3. CD Genomics bioinformatics data analysis process. - CD Genomics. Fig 2. CD Genomics bioinformatics data analysis process.

What can CD Genomics Do?

We can assist in your drug repurposing strategies by offering our proprietary bioinformatics analysis approaches:

Chip data analysis - Mainly refers to DNA chip data and protein chip data. The most widely used in pharmacogenomics research is DNA chip, which analyzes gene expression through bioinformatics methods to determine the polymorphisms in the patient's genome.

Whole Genome Sequencing Data Analysis, Whole Exome Data Analysis, Target Area Sequencing Data Analysis - Analyze all the genes in the genome, find the genetic mutation information such as SNP, and phenotype and genotype analysis, linkage analysis, association analysis, drug effect map.

Proteomics data analysis - Analyze the spatial structure of the protein and the possible targets of the drug.

RNA data analysis - Analyze mutations, expression differences related to disease occurrence and development and find drug targets.

CD Genomics provides you with one-stop bioinformatics data analysis services. In addition to the above analysis, we can also provide customized biological information analysis services related to drug research according to your needs. You only need to provide the original data or only analysis requirements,we will fetch data for you in public databases. Totally, we will provide you with a complete data analysis result report and graphs. For drug discovery and development data analysis, if you have any questions, please feel free to contact us for details.


  1. Jessica V, et al. Applications of machine learning in drug discovery and development.[J]. Nat Rev Drug Discov.18, 463–477 (2019).
* For Research Use Only. Not for use in diagnostic procedures.
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