Early detection of cancers

Early diagnosis improves cancer outcomes by providing care at early stage of the disease. Biomarker discovery has been revolutionized by omics technologies, and by AI methods that are extremely valuable in finding biomarkers in large datasets. However, one pitfall of AI is its tendency to overfit solutions. This is generally occurring when unclean training datasets are injected into the model. In such case, data augmentation will not avoid overfitting as it will only continue to add noisy data.

PredictCan Biotechnologies uses the cell educating technology to generate clean training datasets to avoid overfitting. Our technology generates healthy individual-centric data and patient-centric data on the base of standardized cell line-based multicellular spheroids, cell educating protocol, and sample collection time and process, to obtain noiseless training datasets for optimal biomarkers finding by AI methods.

Phenotypic drug discovery

Phenotypic drug discovery is based on chemical investigations of a disease-relevant biological system in a molecular-target-agnostic fashion.

PredictCan Biotechnologies has developed patient-centric physiologically relevant in vitro systems (GenuineSelect) that are compatible with high throughput screen of compound libraries. Target deconvolution is performed on lead compounds to better understand their mode of action for further optimization after target and efficacy validation on patient-centric model cohorts.

Drug Safety

A major challenge in drug development is the toxicity due to drug side effects. Drug-induced liver injury (DILI) is considered by regulatory agencies as a primary factor in regulatory approvals.

PredictCan Biotechnologies has developed a state-of-the-art 3D individual-centric model to accurately detect intrinsic DILI and idiosyncratic DILI (iDILI) during the early and late stages of drug development.

De-risking liver toxicity with GenuineSelect-TOX

Drug efficacy

In drug development, the ability to challenge the therapeutic value of new molecules on models that mimic global population is a considerable advantage for a better selection before initiating conventional clinical trials. To de-risk failures when entering first-in-human trials a good preclinical model should be capable of predicting clinical drug response.

PredictCan Biotechnologies has developed a state-of-the-art 3D patient-centric model to mimic tumor cells’ phenotype for accurate validation of drug efficacy on cohorts of cancer patients.

Our cell educating technology allows us to generate tailored cohorts of patients for simultaneous testing of a panel of anticancer drugs.

Products for r&d

Immunotherapy research products

Immune cells such as macrophages and dendritic cells are important in immunoregulation and therapeutics. PredictCan Biotechnologies offers a patient-centric differentiation medium to facilitate your research.