4HF Biotec provides services to support the profiling of novel anti-cancer drugs. For this, 4HF is partnering with Reaction Biology as part of their integrated drug discovery pipeline.
Services mainly are dedicated to refine the mechanism of action of a drug, identifying predictive biomarkers of sensitivity and resistance, optimizing the design of drug testing with appropriate model selection and characterizing targets of interest. For cancer target identification, a variety of analyses are also proposed to reveal the true makeup of cancers.
In identifying the most sensitive individual tumors and tumor types we tailor our work to your projects and final goals. If you already have your own dataset or have already identified drug candidates, we can analyze your data in our Cancer Data Miner platform. Please contact us for further information.
Watch our video – 5 minutes to explain in a nutshell the use of bioinformatic tools for biomarker analysis:
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Identification / confirmation of the compound’s mechanism of action.
Mechanism of Action Finder (MOA)
We offer data mining for the identification or confirmation of the MoA of a customer’s compound.
The MoA Finder tool aims to identify the mechanism of action of your test compound based on the results obtained from in vitro drug testing. To this end, we compare the sensitivity profile of your drug candidate to that of more than 900+ drugs for which the MoA is known.
Related Resources:
Poster Download
If you sign up for our newsletter, we will forward you to our activated download page. 3 posters (downloads only on request) + 1 publication (free download)
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Introduction of a platform for preclinical profiling of drug conjugates: A case study with Sacituzumab Govitecan.
A systems biology approach combining ProLiFiler and Cancer Data Miner for an enhanced preclinical characterization of the WEE-1 inhibitor Adavosertib.
ProLiFiler and Cancer Data Miner, combined platforms for preclinical investigation to scrutinize impact of inhibitors on the KRAS, PI3K and MDM2 signaling pathways.
Pharmacogenomics characterization of the MDM2 inhibitor MI-773 reveals candidate tumours and predictive biomarkers.
Identification of molecular characteristics associated to the customer’s drug response.
Biomarker Discovery
The Biomarker Analysis Tool enables the identification of molecular markers predicting response or resistance to a customer’s drug. These predictive biomarkers can be:
- At the RNA level with the expression of specific genes and with the or development of gene signatures
- At the DNA level with presence of gene amplification, exon mutation, or gene deletion
The Biomarker Analysis Tool compares the IC50 or IC70 raw data set to the gene expression levels, somatic gene copy numbers, and exon mutations of the human cell lines. These biomarkers are indicative for drug efficacy and serve as predictive biomarkers in tumor models and patient cohorts to stratify responders from non-responders. Performing this type of analysis in an early discovery phase can lead to optimize the development strategy.
In vitro drug profiling can be performed with our collaborator, Reaction Biology, which offers the ProLiFiler – Reaction Biology’s Cell Line Panel Screening service.
Related Resources:
Poster Download
If you sign up for our newsletter, we will forward you to our activated download page. 3 posters (downloads only on request) + 1 publication (free download)
Subscribe & DownloadIntroduction of a platform for preclinical profiling of drug conjugates: A case study with Sacituzumab Govitecan.
A systems biology approach combining ProLiFiler and Cancer Data Miner for an enhanced preclinical characterization of the WEE-1 inhibitor Adavosertib.
ProLiFiler and Cancer Data Miner, combined platforms for preclinical investigation to scrutinize impact of inhibitors on the KRAS, PI3K and MDM2 signaling pathways.
Pharmacogenomics characterization of the MDM2 inhibitor MI-773 reveals candidate tumours and predictive biomarkers.
Identification of suitable models for preclinical studies​
Model Selection
4HF platform integrates molecular information (genomic alterations, transcriptomic profiles) and drug sensitivity profiles for more than 1.800 preclinical models (130+ cell lines; 500+ PDX), covering 30+ types of cancer. These data are complemented with those from large data bases of patient’s tumors and normal tissues (together 27.000+).
This large amount of data can be used to:
- select the best preclinical models for in vitro and in vivo drug sensitivity experiments
- identify the most appropriate cancer entities for your compound of interest, therefore maximizing the chance of success in clinical trial phases.
- anticipate potential off-target effects and toxicities from expression in normal tissues.
Molecular characterization of cancer targets
Target Investigation
The Gene Explore service aims to help customers characterize their targets to validate its usefulness in anticancer drug discovery. By using the 4HF Cancer Data Miner platform, the customers have access to the gene expression, exon mutation, gene copy number alteration information from:
- 1800+ preclinical models (cell lines, cell line-derived tumor xenografts, patient tumor-derived xenografts)
- 11 000+ patient tumors of 32 cancer entities
- 16 000+ normal samples of 41 types
Related Resources:
Poster Download
If you sign up for our newsletter, we will forward you to our activated download page. 2 posters (downloads only on request) + 1 publication (free download)
Subscribe & Download
An advanced in silico drug discovery platform, 4HF Biotec's Data miner for identifying novel targets for tumors and tumor-stroma
4HF Cancer Data Miner platform for an accelerated In Silico ADC target discovery and evaluation.
Elevated MACC1 Expression in Colorectal Cancer Is Driven by Chromosomal Instability and Is Associated with Molecular Subtype and Worse Patient Survival.
