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Precision Medicine

We are focused on Precision Medicine as an approach to discovering and developing potential treatments that deliver superior outcomes for patients, by integrating clinical and molecular data to understand the biological basis of disease, the pharmacology of our Drug candidates and the appropriate patient population to treat. Precision medicine efforts has the potential to lead to better matching of drug targets with selected patient populations that may experience clinical benefit.

We are interested in establishing alliances to develop and access:

Patient cohorts with high quality longitudinal clinical (e.g. electronic medical record), molecular, imaging and other phenotypic data preferably paired with broadly/appropriately consented biospecimens (e.g. whole blood serum/plasma, saliva, tissue, PBMCs, stool, etc.), and with the potential for patient recall

Systems Biology/Pharmacology

  • Databases with high quality treatment and disease outcomes associated with genetic, as well as molecular (metabolomic, proteomic transcriptomic, epigenetic, clinical chemistry markers) or functional measures, in particular with associated imaging data
  • Databases of searchable eQTLs, pQTLs across tissues
  • Disease biology guided combination therapy design platforms
  • Systems biology approaches and proven in silico tools to evaluate pharmacological perturbation and to elucidate mechanisms of in vivo toxicity
  • Mining of data for correlation and understanding of causality

Breakthrough diagnostic technologies that are highly quantitative, require minimal specimen/ tissue, offer quick turnaround time and can be multiplexed. This will include but not limited to:

  • Near-patient Point-of-Care technologies
  • Next Generation Sequencing technologies that can use multiple specimen matrices including tissue and blood
  • Circulating tumor cells
  • Circulating cell-free nucleic acids
  • Antigen receptor sequencing
  • The above will ideally need to be paired with capabilities and footprint for distribution in global markets, regulatory and reimbursement strategies, and commercialization capabilities

In vivo imaging technologies (including MRI, PET, CT, optical imaging technologies, imaging agents, genetically encoded tags, etc.) with particular interest in

  • Imaging agents for small and large molecule compound distribution studies
  • Imaging agents monitoring physiology mechanisms and disease
  • Analytical tools and technologies

Biospecimen Analysis

  • Circulating tumor cell and cell free nucleic acid quantification and analysis
  • High dimensional single cell analysis platforms
  • High dimensional IHC/IF for tissue digital image analyses (cancer, safety)
  • Advanced ADME-related genotyping
  • Extracellular vesicle, exosome analysis
  • 3D cell models for safety and efficacy assessment that ideally incorporate genetic diversity
  • Skin tape strip, sebum analysis
  • High dimensional flow cytometry
  • Emerging “omic” analysis (e.g. phosphoproteome, autoantibody profiling)

Physiological Biomarkers

  • Technologies adding precision to pain management and treatment in pre-clinical clinical studies
  • EEG-based biomarkers

iPS cell resources and technologies to generate iPS cells that may be used to enable Precision Medicine strategies

  • Validated cell differentiation protocols
  • iPS cells derived from sub populations with specific genotypic/phenotypic data
  • Technology to create iPS cells in a rapid and reproducible fashion without insertional approaches

Biospecimen collection/stabilization technologies

  • Novel sample collection approaches that allow frequent (at home) sample collection with appropriate stabilization

Remote Patient monitoring technologies

  • Novel actigraphy and other home monitoring systems that allow frequent at home monitoring of relevant physiological states/biomarkers

Advanced computational biology approaches/platforms:

  • integration of high-dimensional data across various platforms in combination with classical clinical readouts for the predictive modeling of patient response/disease progression
  • AI approaches to gaining disease insight, target selection and/or patient populations likely to respond to treatment.
  • Microbiome, including virome characterization