Access the depth of molecular knowledge For the transformation in precision medicine, and a causal understanding of diseases
Empowered by our proprietary Dataome platform, we perpetually capture and enhance globally available sources of clinical and molecular data. By intimately connecting these disparate data domains, Dataome extends the dimensions of analytical possibility and delivers more intelligible data for healthcare. This is the evidence base upon which new innovations in data analytics are built, delivering actionable insights to transform the success of clinical development and patient care. Several applications arise from Dataome. In in silico disease model building (MH Insilico), for instance, it serves as the core data integration, knowledge base and analytical framework. Dataome was designed to enable the constant capture and curation of globally available data sources of clinical and
Dataome technology – Fact sheet
molecular knowledge with the aim of delivering high-quality data for clinical decision-making and knowledge discovery in a disease-agnostic manner. It consists of three core components: Dataome Capture Controls the perpetual capture, enhancement, and integration of global clinical and molecular data sources. Dataome Knowledge A comprehensive data and knowledge resource containing highly interconnected clinical and molecular data, linking clinical phenotypes to underlying molecular knowledge. Dataome Analytics A palette of analytical solutions designed to derive new insights from the data contained in the knowledge platform.
Our unique technology …
Developing software solutions that process and make the growing body of worldwide medical knowledge usable
DATAOME CAPTURE
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DATAOME CAPTURE
DATAOME KNOWLEDGE
DATAOME ANALYTICS
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DATAOME KNOWLEDGE
Dataome Knowledge encompasses data from more than one hundred public and commercial/private resources, including in-house proprietary data blocks.
Dataome technology – Fact sheet
Other resources include data for millions of patients coming from real-world data (RWD) such as public pharmacovigilance repositories (e.g., VigiBase or FAERS), as well as information regarding clinical trials (e.g., from NLM’s clinicaltrials.gov or WHO’s ICTRP Database).
Structured + unstructured human biology data
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Text mining, automated database capture
trial success (POS)
Dr. Friedrich von Bohlen, Chief Executive Officer Molecular analysis
of drug mechanisms
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Public datasets incorporated in the Dataome Technology Platform span a broad range of content, size and formats – from more general, such as: • literature (e.g., PubMed) • cheminformatics (e.g., chemical structures from PubChem) • biomedical ontologies (e.g., ICD, MedDRA, ATC, MeSH, UMLS, HPO, GO, DOID) • information about proteins and genes (e.g., from resources like UniProt, Entrez Gene, Ensembl, UCSC, or RefSeq),
to the more specific, such as: • genomic variant annotations (ClinVar, dbSNP/dbNFSP, etc.) • information about drugs and their labels • targets or interactors (DrugBank, AHFS, FDA Orange Book, or Drugs@FDA, etc.) • biomolecular pathways and interactions (KEGG and Reactome, etc.)
MH APPLICA
Genome-guided clinical CUmolecular biology willdecision support “The connection between IT and RA medical progress bring about some of the most important in coming years. Molecular Health is a pioneer in this area, using Dataome along with unique software solutions that make better medicine possible.” Prediction of clinical
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Structured + unstructured clinical data
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Structured data is assimilated using automated data integration pipelines that process, normalize, and quality assure the data in synchrony with database update cycles. These functions utilize an extensive
infrastructure that enables extraction, transformation, and loading (ETL) of source data into a consolidated database framework for information modeling and knowledge extraction. For unstructured data, text and data mining (TDM) technologies provide a framework to feed biomedical facts to a proprietary curation infrastructure for review by biomedical experts. Curated and quality-controlled data is then integrated into Dataome Knowledge.
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Dataome Capture technology uses an ensemble of public or proprietary algorithms and resources to enable the global harvesting, quality assurance, and integration of emergent clinical and molecular data.
KNOWLEDGE
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… for better medicine
CIA L
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Enabling in silico drug research & development
“The recording, linking, and structuring of the clinical and molecular knowledge available worldwide and its provision Transformation, knowledge Cleaning, standardizationfor the wide variety of medical applications is what we have modeling, data interpretation referencing, expert curation perfected using Dataome.”
The descriptions of our can Dr. applications Stephan Brock, be found on the back of this fact sheet. Chief Technology Officer
Healthcare support tec
Our unique technology … DATAOME CAPTURE
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DATAOME CAPTURE
DATAOME KNOWLEDGE
DATAOME ANALYTICS
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DATAOME KNOWLEDGE
Dataome Knowledge encompasses data from more than one hundred public and commercial/private resources, including in-house proprietary data blocks.
Dataome technology – Fact sheet
Other resources include data for millions of patients coming from real-world data (RWD) such as public pharmacovigilance repositories (e.g., VigiBase or FAERS), as well as information regarding clinical trials (e.g., from NLM’s clinicaltrials.gov or WHO’s ICTRP Database).
Structured + unstructured human biology data
Text mining, automated database capture
MH APPLICATIONS
Genome-guided clinical decision support
Prediction of clinical trial success (POS)
Molecular analysis of drug mechanisms
RT
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Public datasets incorporated in the Dataome Technology Platform span a broad range of content, size and formats – from more general, such as: • literature (e.g., PubMed) • cheminformatics (e.g., chemical structures from PubChem) • biomedical ontologies (e.g., ICD, MedDRA, ATC, MeSH, UMLS, HPO, GO, DOID) • information about proteins and genes (e.g., from resources like UniProt, Entrez Gene, Ensembl, UCSC, or RefSeq),
to the more specific, such as: • genomic variant annotations (ClinVar, dbSNP/dbNFSP, etc.) • information about drugs and their labels • targets or interactors (DrugBank, AHFS, FDA Orange Book, or Drugs@FDA, etc.) • biomolecular pathways and interactions (KEGG and Reactome, etc.)
CU RA
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Structured + unstructured clinical data
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Moreover, the Dataome Technology Platform contains structured information regarding therapeutic guidelines and variant classification (e.g., ACMG, NCCN, or ESMO), as well as further curated data sets pertaining to clinical biomarker interpretation, pathway/interaction relationships, drug information and clinical trial information. MH Drug is an example of a proprietary database that is used in disease model projects, e.g., for the identification of druggable targets. It is a consolidated knowledge resource containing drug-centric features from different source databases, e.g.: • PubChem • Excelra GOSTAR • DrugBank, ChEBI • Drugs@FDA • FDA OrangeBook • TABS It captures comprehensive drug knowledge
around bioactive molecules at various stages of clinical development, including information about: • chemical structure • targets • metabolizing enzymes • transporters • drug binding constants • pharmacological activity • drug classifications The database contains curated information about: • drug-target interactions (DTI) • drug-drug interactions (DDI imported from external sources) • drug developmental status (DDS, imported from external sources) MH Drug currently includes information about: • over 90,000 bioactive moieties • over 500 curated cancer medications • over 130,000 DTIs
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Structured data is assimilated using automated data integration pipelines that process, normalize, and quality assure the data in synchrony with database update cycles. These functions utilize an extensive
infrastructure that enables extraction, transformation, and loading (ETL) of source data into a consolidated database framework for information modeling and knowledge extraction. For unstructured data, text and data mining (TDM) technologies provide a framework to feed biomedical facts to a proprietary curation infrastructure for review by biomedical experts. Curated and quality-controlled data is then integrated into Dataome Knowledge.
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Dataome Capture technology uses an ensemble of public or proprietary algorithms and resources to enable the global harvesting, quality assurance, and integration of emergent clinical and molecular data.
KNOWLEDGE
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… makes the difference
CIA L
IN T E LL
N IGE
Cleaning, standardization referencing, expert curation
The descriptions of our applications can be found on the back of this fact sheet.
Enabling in silico drug research & development
Transformation, knowledge modeling, data interpretation
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Healthcare decision support technologies
DATAOME ANALYTICS
The extensive data contained within Dataome Knowledge provides the evidence base that enables the development of both novel decision support technologies and the efficient development of disease models for any human disease or phenotype. These efforts are supported by the large palette of analytical technologies and AI-
based tools contained within the Dataome Analytics part of the Dataome Technology Platform – including MH Guide that helps physicians choose the right drugs for their patients, MH Effect that helps regulators relabel drugs and predict drug side effects based on the Molecular Analysis of Side Effects (MASE) method, or MH Predict that helps predict the likelihood of clinical trial success.
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MH APPLICATIONS
Individual solutions for complex challenges Supporting molecular pathologists, oncologists, and other medical professionals in the clinical annotation of genetic variants, enabling physicians to make precision oncology decisions. MH Guide is a tool for identifying the most effective, ineffective, or potentially toxic medications for a cancer patient by analyzing the molecular profile of the patient’s tumor in the context of all relevant and related information contained in Dataome. By mapping the patient’s specific tumor mutations to the world’s knowledge in the field of oncology, MH Guide creates a patient-specific clinical report that includes a list of potentially effective medications and other therapeutic approaches. MH Guide also includes two modules specifically designed for the analysis of hereditary diseases (MH Guide/BRCA and MH Guide/Mendel). Supporting the pharmaceutical industry and investors alike in making the right investment decisions by predicting the success of clinical trials. MH Predict is a tool that uses AI and ML algorithms for intelligent simulations and analysis of clinical study programs with the goal of mitigating the risks inherent in the process of drug development. By giving users complete control over these algorithms and making the process fully accessible, MH Predict exponentially increases the level of confidence with which the user will implement any of the actionable outcomes determined by the underlying AI and ML algorithms. Helping regulators and pharmaceutical companies relabel drugs, identify repurposing drugs, and predict drug side effects. MH Effect is a tool for the comprehensive clinical and molecular assessment of drug action and adverse events. By tapping into millions of patient records of drug outcomes, including emerging safety issues, MH Effect helps discover adverse events associated with marketed drugs that might have gone unnoticed but could be relevant to other drugs by simulating and analyzing drug interaction, and predict potential safety issues of drug candidates in development. In turn, it can identify the desirable effects of drugs. Enabling in silico drug research and development. MH Insilico is a service for the rapid development of testable molecular hypotheses from unique custom built causal-molecular disease models. This allows to create hypotheses for both, patient care and drug development. Through MH Insilico, new drug targets can be found and validated, clinical trials can be better planned and stratified, and drugs can be more precisely positioned. Moreover, MH Insilico reveals molecular interactions in patients that can help to guide individual treatment schemes. Thus, MH Insilico blends the knowledge of Dataome with the company’s analytics and experts in collaboration with customers’ experts to reach novel insights in care and drug development. Based on the power to build causal disease models Molecular Health sees the convergence of patient care and pharma R&D. Disease understanding at the molecular level allows better treatment and better drug development.
Molecular Health GmbH, Headquarters Heidelberg, Germany, Europe Kurfuersten-Anlage 21, 69115 Heidelberg USA Tel. +1 346-221-1955 CustomerCareUS@molecularhealth.com
Asia Pacific Tel. +49 6221 43851-2363 CustomerCareAsia@molecularhealth.com
MH-21-010-1
Europe Tel. +49 6221 43851-150 CustomerService@molecularhealth.com
