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

CUMULATIVE INSIGHT

INPUT

OUTPUT