Who we are?
Dr. Maria Tsiper, Founder of PolyOmic Solutions, brings over 20 years of experience in biomedical research and commercialization, specializing in molecular diagnostics, drug discovery, technology transfer and commercialization.
With degrees in Engineering Physics (BS), Biophysics (MS), and Molecular Genetics & Microbiology (PhD), Maria is an expert in interdisciplinary science - bridging technical innovation, statistical analysis, and data-driven insights with strategic business acumen. She founded PolyOmic Solutions to help transform ideas into high-impact publications, compelling presentations, patentable innovations, and commercially viable solutions.
"My career has always been about turning vision into reality - efficiently, strategically, and with impact," - says Maria. "From launching clinical diagnostic tests to driving successful clinical trial enrollment and forging high-value industry partnerships, I thrive on delivering results."
With deep expertise in disease biology, drug development, and molecular diagnostics, Maria translates big-picture vision into executable strategies. Her passion for precision and individualized medicine fuels her approach to solving healthcare challenges, driving innovation from ideation to patient impact.
Why PolyOmic?
"Poly" means 'many' in Greek, while "Omics" is derived from the Greek suffix "-ome" which indicates totality, entirety, or a complete set. The term "OMICs" is commonly used in biological disciplines that study combinatorial sets of genes/DNA (genomics), proteins (proteomics), metabolites (metabolomics), RNA (transcriptomics), etc.
For example:
- Proteomic data
- reveals protein composition of a sample including post-translation modifications.
- Genomic data
- consists of a complete sets of DNA within a cell type or an organism.
- Transcriptomic data
- consists of a complete set of RNA transcripts of a cell type or an organism.
- Metabolomic data
- consists of metabolite profiles (metabolites are all products of cellular processes).
- Metabolomic data
- consists of sets of metabolites profiles collected at different environmental or genetic modifications.
- Interactomic data
- describes all interactions between proteins and other molecules within cellular sample.
- Phenomic data
- set of phenotypic characteristics (phenotypes, traits) of a cellular sample.
- Palindromic data
- symmetrical sequences of numbers or letters with distinct meaning or beauty. Not really related to biotech.
In today's era of technology and laboratory automation, biological experiments often utilize high-tech robotic instrumentation to generate large-scale OMICs data sets. These datasets frequently integrate multiple modalities, such as next-generation sequencing, multiplexed microscopy, multi-channel flow cytometry or digital pathology. Additionally, they can be complemented by population-level and patient-specific data from scientific literature, medical records and insurance claims. As a result, OMICs data interpretation requires advanced multivariate statistical approaches, leveraging machine learning (ML) and artificial intelligence (AI) techniques to generate reliable and meaningful insights.
Favorite Quote:
"If you can't explain it simply, you don't understand it well enough" A. Einstein
