Model CRO - Digital Bioinformatics Analysis & Drug Discovery
Bioinformatics Analysis & Drug Discovery in the era of Artificial Intelligence. The digital CRO team brings together scientists and engineers with diverse skill sets, ranging from biology and chemistry to statistics and machine learning. We work with both small startups and big pharmas to leverage digital power in order to enable the development of new therapies. We contribute to the entire drug discovery process, from target identification and validation, to compound design and clinical trials. We make bioinformatic workflows and software with human-readable code, as well as machine learning models that “understand” biological data and provide cutting-edge solutions for Precision Medicine.
From target identification to clinical trials
Target identification
- Identification of protein-DNA interaction sites
- Identification of off-target binding sites
- Prediction of protein-protein interaction sites
- Prediction of similarities in drug effect and mode of action
- Identification of genetic and epigenetic variability
- Profiling of gene expression, protein, and metabolite abundances
- Dimensionality reduction and clustering in single cell analysis
- Natural Language Processing for information retrieval
- Machine Learning-based binding pocket search
- Data mining for target identification
- Computer Vision for medical image analysis
Target Validation
- Computational methods for the creation of KO/KD/KI
- Computational methods for the creation of disease models
Hit generation
- RNAi-based therapeutics
- Machine Learning-based virtual screening
- Computer Vision for high-content screening
- Drug repurposing
Hit to Lead optimization
- Peptide structure modelling and optimization
- Prediction of druggability
- Deep learning generative models for compound design
- Machine Learning-based prioritization of molecules
- Property and affinity prediction
- Prediction of ADME/T properties
- Prediction of protein properties
- Protein optimization
Preclinical
- Prediction of toxicity including immunotoxicity
- Design of CDx for clinical trials
Clinical Trials
- Biomarker-based patient stratification and survival analysis
- Statistical inference on experimental data
- Computer Vision for medical image analysis
- Prediction, monitoring, and analysis of treatment response
- Biomarker Discovery, including on multi-omics datasets
AGILE for Life Sciences
We work according to Agile methodology, which we adopted for Life Science projects. It accelerates the delivery of business value. Through a process of continuous planning and feedback we are able to constantly maximize value throughout the research or development process
