ModCellTM – a unique approach for personalizing precision medicine and accelerating drug development through modeling virtual cell types, tissues and patients
Our proprietary ModCellTM technology is a new, revolutionary systems medicine modeling tool for optimizing predictive personalized medicine and drug development. A simulation tool that provides a gateway to the complex molecular processes occurring within each of our cells, fostering insight and discovery for clinical application.
How the model works
ModCellTM has been built on the premise that the onset and progression of a disease is associated with a malfunction in the complex biological networks occurring in specific cells or tissues in our bodies. The model is essentially a computational representation of the complex molecular networks in cell types and tissues. All the different biological entities that make up this complex network – for example, genes and proteins – are represented as ‘objects’ within the model, which when taken together carry out all the cellular processes which keep us healthy or, if altered, contribute to the development of diseases.
The mechanistic avatar has been built using a large and growing public knowledge base on cellular pathways and biological processes and can integrate the molecular effects of changes in gene activity and mechanistic drug action. The model leverages the rapidly accumulating information base generated through decades of basic research and accessible via the scientific literature or dedicated repositories. It is through reference to this knowledge that we can make sense of patient-specific data.
For personalized predictions, models are individualized with qualitative and quantitative high dimensional data obtained from deep sequencing and/or other experimental omics platforms (see purple layer in the figure below). A range of software tools within the modeling environment (see light orange layer in the figure below) is used for model development, simulation, and optimization.
At the core of ModCellTM is a mechanistic model of cellular pathways and processes integrating cancer-associated signal transduction pathways, mutations and drugs. Different software tools are used for model development, simulation and optimization. The generic model is individualized by omics data from public and proprietary sources.
Application of ModCellTM in personalized cancer treatment
For patient-specific simulations of drug treatments, the generic ModCellTM model is initialized with omics data from a specific tumor, typically genome, exome, and transcriptome. Data generated is analyzed using our in house developed NGS data analysis pipelines NGSightTM and OncovarTM, to identify tumor-specific molecular variations such as mutations or quantitative changes in gene expression patterns. Integration of such molecular variations into the general mechanistic model – using our certified standard operating procedures – enables us to generate a virtual tumor model that closely resembles a specific tumor.
This virtual tumor is used by ModCellTM for in silico testing of its response to therapy. To predict quantitatively how a specific drug will affect an individual tumor, we represent the drug as another object, which binds to specific mutated or altered proteins, eliminating or reducing its function. To identify the consequences of the drug action, we have to translate the object representation of the model into mathematical equations and then solve them computationally. For this, we compute, for example, how rapidly a protein in the model carries out a specific reaction, or how tightly a drug binds to a specific target protein.
The personalized virtual tumor model can be treated in silico with a panel of drugs approved for cancer or other disease areas, or available through clinical trials. Using the virtual tumor approach we can determine the likelihood that a given tumor will respond to a specific drug.
ModCellTM identifies the most effective drugs, providing supporting information for physicians and tumor boards, complementing the CMTA.
The virtual tumor generated by ModCellTM through the integration of high dimensional data into a model of molecular processes in human cells facilitates true personalization of therapy for the individual patient.
Focus on oncology
A major focus in the development of ModCellTM has and continues to be oncology, with the integration of information on a range of cancer-associated signal transduction pathways, consequences of mutations, and mechanistic drug effects that are used to generate virtual tumor models. The generic models become specifically tuned to specific cancer (sub)-types, integrating, for instance, drug resistance mechanisms.The combination of individual tumor data with a systematic exploration of the effects of drugs (and their combinations), opens up the possibility of identifying new therapeutic avenues, including drugs not usually considered for cancer treatment and those being tested within clinical trials.
The diagram above, highlighting a small fraction of the large-scale molecular network represented by ModCellTM, depicts how over-expression of the tyrosine kinase MET can be inhibited by the cancer drug crizotinib. Such molecular dysregulations, as well as the effect of a targeted drug (i.e. with a known molecular target) on subsequent signaling within the network, can be simulated and predicted by ModCellTM.
Application of ModCellTM in virtualization of drug development and clinical trials
Drug development is time consuming, costly and risky, with most drugs entering pre-clinical and even clinical development failing to gain approval. Approaches that streamline the drug approval pipeline and reduce associated research and development costs are therefore essential. We offer a set of technologies that virtualize significant components of the drug development process, allowing multiple scenarios to be tested in silico in a rapid, safe and inexpensive manner. With our proprietary ModCellTM system, we offer the possibility of carrying out ‘virtual clinical trials’ to predict the efficacy of repurposed or novel drugs within patient groups.
Based on molecular profiling data sets, in combination with available information on drug targets and approximate drug binding constants, in silico testing can be carried out at any stage of the drug development process, from drug pre-synthesis to post-selection for clinical development.