Lack of Models Translationally Relevant to Human Tumor Biology
Existing Options
Serious Issues
Mouse Models
Non-human Data
High Failure Rate
Loss of Time and Money
Mice are NOT human
2-Dimensional
Tumors are NOT
Tumors cells DO NOT grow in isolation
Cell culture
Basic Organoids
Critical Problem
Lack of effective and relevant testing models forces pharma to primarily develop oncology drug candidates with non-human data.
95% of known cancers lack targeted treatments
Developing candidates with non-human and incomplete efficacy data largely contributes towards failure rate of 96.7% drugs at approval.
High failure rate of drugs at approval stage results in loss of millions of dollars spent across multiple years.
Problem and Solution Focus
Problem Focus
SPANIOS Solution Focus
Lack of model systems that capture the biology of human tumors
Model systems that recapitulate and mimic human tumors
Platform that provides highly translatable human efficacy data
Lack of models that provide human efficacy data at the preclinical stage
Bottom Line: We Add Value to Our Client’s Work
Target Client
Type of Data
Shorter Timeframe
Higher Take Rate
Highly Translatable Data
How it works: Data Flywheel
IND Readiness
Range of Service
Approx. 4 months compared to
12-24 months with other methods
Rate of growing PDT from tissue is 80-85% compared to <20% for PDXs
Tests done on the PDTs applicable to humans 80% of the time compared to <55% with others
Data from PDTs can now be taken directly for IND filing instead of having to get mouse data
Translationally relevant data
Repeatable empirical data
Usable and scalable data
Efficacy studies
Biomarker studies
Combination studies
Small, medium and large size pharma and biotech companies
New Drug Efficacy
Combination Therapies
Drug Repositioning
Improved Therapeutics
Additive/ Synergistic
New indications
Biomarker Discovery