Cell therapy development and validation largely benefits from robust genomic and proteomic characterization required to gain a high-dimensional and unbiased assessment of the complex interactions between delivered therapies and cancer cells, as well as a comprehensive view of the immune response and potential long-term resolution of disease.
Cell therapy
Diverse protein profiles offer insights into cell signaling pathways and cell state dynamics, significantly impacting the ability to produce more specific treatments. Leveraging the precision and comprehensive coverage of proteomic techniques accelerates the identification of predictive biomarkers and strategies for therapeutics development.
Protein profiling
Translational genomic studies can evaluate genomic and epigenomic predispositions and changes over time that influence individual response to stimuli, supporting the development of more personalized medicine.
Genetic analysis
Predicting therapeutic outcome based on individual genetic profiles can be easier and faster with a pharmacogenomic solution that consolidates single-nucleotide polymorphism, copy number variation and tandem repeat workflows into a single, automated system, significantly reducing hands-on time and improving data accuracy.
PGx
Specificity, efficacy and safety of a potential drug candidate can be analyzed by understanding proof of mechanism, to ensure the drug interacts with the intended target and for the intended effect. If a mechanism includes rare or hard-to-identify molecules or cell types, using tools with higher dynamic range and full coverage enables detection of all possible interactions.
Proof of mechanism
Patient stratification is important to understanding therapeutic outcome and identifying those who are more likely to benefit from a therapy. It can be facilitated using wider coverage proteomic and genomic analysis to ensure comprehensive profiling and determine correlated signatures.
Patient stratification
Biomarkers are needed to predict therapeutic outcomes consistently and accurately for cancer and other diseases that exhibit high heterogeneity and broad cellular signatures. Uniquely scalable multi-omics provides higher coverage to confidently reveal novel phenotypes and identify therapeutic targets relevant to developing biomarkers and directing treatment strategies.
Biomarker discovery
Clinical and translational research demands accurate and reproducible immune profiling, especially when samples are processed and analyzed by different technicians or at different study sites. Robust immunophenotyping with an easy-to-implement solution for routine and flexible sample collection can capture the highly individual nature of immune states and response.
Immune profiling
