It is recognized that altered metabolic states reports on the chronic and acute disease statuses. Decades of research have shown that metabolism is not a self-regulating network operating independently but rather heavily integrated into every cellular process and involved in organ system functions. Therefore global monitoring of metabolic processes is recommended for more comprehensive understanding of the initiation and advancement of disease. Mass spectrometry based metabolomics, in particular, demonstrates tremendous promise in delivering high throughput quantitative information on alterations in metabolism associated with disease onset/progression and response to pharmaceutical intervention. Recent advances in mass spectrometry and informatics tools have facilitated emerging in house OMICS platforms capable of translating biological output into viable therapeutic candidates and assist in stratifying patient populations. At BERG, we have implemented an industrial level high throughput metabolomics platform providing both high quality and depth of information allowing for reliable and broadest capture of the metabolome for the pre-clinical and clinical matrixes analyzed. Global metabolomics platform dedicated for theranostic and clinical studies as well as tracer metabolomics are harvested to facilitate CDx biomarkers discovery in a unique way. Highlights of the BERG’s in-depth patient stratification approaches as well as biology based drugs will be presented.
Thank you. BERG is extremely careful in selecting collaborators providing samples for analysis. By giving an example of BERG clinical trials in my presentation in order to illustrate CDx development utilizing multi-omics profiling, I emphasize on having all the clinical records for trials participants which have necessary metadata on their physiological status prior and during clinical trials. Metadata is in the processing bAIcis system (see slides 28-30) prior all further statistical and networking procedures.
In the case of the general populations health monitoring it can be done by sampling and analyzing healthy cohorts as well as co-morbidity studies where large clinical and lifestyle info is available. It will be impossible to associate diet/lifestyle until massive studies are done to layer that on top. It is not just what person eats, but how his body processes it.
Vladimir Tolstikov
In order to become a routine tool in the clinical metabolomics applications, the MS technology needs to reproduce the metabolite quantitation in a robust way. At present, what is the status of the problem of sample derivation and absolute quantitation in applying LC-MS or LC-MS/MS technology.
Thank you. Metabolomics as a standalone protocol as well as a part of multi-omics profiling is in R&D department. Once candidate biomarkers are selected it goes to CLIA lab where assay development starts under all the FDA approved SOPs. There is no questions on sample derivation and absolute quantitation in applying LC-MS or LC-MS/MS technology in CLIA lab.
In the case of small molecules, where clinical metabolomics is very involved in the process of discovery, examples are presented on the slide 9 of my presentation where FDA approved small molecule biomrakers are listed. Measurements of these molecules done in clinical labs for years by GC-MS, LC-MS and LC-MS/MS protocols which are approved with FDA. Slide 10 of my presentation illustrates approved utilization of Phenylalanine as a biomarkers for Phenylketonuria as well as its poor ability to report on other conditions.
Vladimir Tolstikov
Thank you for very interesting presentation!
Precision medicine is a very interesting approach, matching the right drug to the right patient. Did you actually succeeded in developing precision medicine or is it still in the stage of development?
How long time is needed to develop the precision medicine? From you take a sample to you have an answer?
How do you perform network analyses when you have the data from different omics platforms?
Do you use different databases to look for known pathways?
Thank you. Precision medicine is emerged on the basis of the failure one-drug-for all patients idea. It works fine when medicine is obviously essential part of suffering living organism. Silly example is a water - H2O. When it is a severe shortage of drinking water any living organism is quickly getting sick. In this case water is universal medicine for all the suffering patients. It is not the case for numerous drugs designed to engage the certain targets. Not everyone will respond/tolerate this kind of treatment. It was observed during drug trials as well. Responders and non-responders grouping to drug administration is well know phenomena today.
Precision medicine is currently in the stage of development. I would point out on two currently shaping directions:
1. Known drugs re-positioning.
2. New drugs development based on back-to-biology principle.
It is not a big problem today for professionals to analyze a sample. Bigger problem is a population study. Merging data from different omics platform and network analysis is accomplished by the Analyitcs who may use obvious and/or proprietary algorithms. Here we have two or more different approaches as well.One would be the utilizing previously acquired knowledge and being guided by the hypothesis driven approach. The other one would be based on the data driven approach. Latter would benefit from exploiting casual networking protocols. Or one can do both.
Vladimir Tolstikov
Thank you very much for the answers!
I have just a quick equation more. The artificial intelligence machine learning analytics program that you are using at Berg for network analyses, is it a program developed at Berg? Or is it commercial program? Or are you going to commercialize it at some point?
Thank you for your interest in BERG. The program was developed by BERG. It is a proprietary program. Please visit http://analytics.berghealth.com/ for details.
Vladimir Tolstikov
