Oncology

Cancer is one of the most difficult disease to treat with high mortality rates of 92.3% within five years of diagnosis. A major challenge encountered in cancer drug discovery and development is  high attrition rates of development candidates in clinical trials due to lack of efficacy. This lack of efficacy in clinical studies has been attributed to low accuracy of preclinical models to predict efficacy of compounds in the clinic. As a result, preclinical models with high predictive value for efficacy are urgently required.

TheraIndx offers a range of in vitro, ex vivo and in vivo preclinical models for cancer drug discovery and development. The Oncology team of TheraIndx with extensive experience in Cancer Drug Discovery and Development help our partners using our patented Artificial Intelligence based predictive models (OncoDynamiX) , 2D/3D Organoid models, Hollow Fiber models, Pharmacology models integrated with Biomarkers to help in better translation from preclinical stage to clinical development.

Organoid Models For Cancer Drug Discovery

The 3D Organoid model was developed to overcome the shortcomings of the 2 D method. Here the cancer cells derived from human cancers are grown into organoids which have the characteristics of tumors in terms of architecture (histology) and genetic heterogeneity. They have been shown to maintain the characteristics of the tumor taken from the patient.

The patient derived organoids (PDOs) are valuable tools to evaluate the anti-cancer activity of clinical drug candidates in drug discovery programs in Cancer. The results obtained from the organoid screen are more predictive of efficacy in patients as they take into account the accessibility of drug to tumor cells across barriers and the heterogeneity of mutations.

Patient Derived Organoids (PDO) significantly improve the translational success for anti- cancer therapeutics in clinical trials.

Advantages:
  • Demonstration of Early Proof of Concept: Testing of Lead Compounds in PDOs expressing the pharmacological (drug) target help to establish proof of concept early in program and increase confidence for clinical efficacy. They also help in identification of Biomarkers for efficacy that can be applied in clinical trials.
  • Identification of target populations for Clinical Trials: At the nomination stage, Clinical Drug Candidates can be screened against a bank of PDOs, expressing the drug target, to identify specific patient molecular types in which they are maximally effective. This will enable selection of appropriate patients in clinical trials and increase the confidence for high clinical response.
  • Identification of Cancer Indications: Drug Candidates can be screened against PDOs from different cancers expressing the same abnormally expressed drug target to identify cancer indications for clinical trials.

Hollow Fibre Models

Hollow Fiber Models form the link between in vitro efficacy and in vivo efficacy in Xenograft models of cancer. They can be effectively employed to rapidly screen many molecules for preliminary evaluation of Pharmacokinetics and Pharmacodynamics.

Advantages:
  • Rapid in vivo screen of anti-cancer molecules (few days)
  • PK and PD information obtained from the same animal
  • Prioritization of molecules for confirmatory studies in xenograft models

Animal Models

XENOGRAFT
  • Brain
  • Breast
  • Cervical
  • Colon
  • Hepatocellular
  • Gastric
  • Leukaemia
  • Lung
  • Melanoma
  • Ovarian
  • Pancreatic
  • Prostate
  • Renal
ORTHOTOPIC
  • Leukaemia/Lymphoma
  • Breast
  • Liver
  • Stomach
  • Kidney
  • Prostate
  • Skin