ABOUT
IPQ Analytics, LLC (IPQ) is a models as a service (MaaS) company that works globally with industry
(life sciences, pharma, device, diagnostics; across silos), payers, providers, investment banks, associations and government agencies.
IPQ builds computational models of disease, from the clinic back to molecular processes, that reflect the real-world complexities of the patient, the disease and the healthcare environment, including physician and drug developer.
These models are instantiated within a novel knowledge graph that serves as a learning system and continues to evolve through application into new diseases and conditions. IPQ uses this approach to identify critical gaps and conflicts in existing data/knowledge, to treat disease as a process to support the longitudinal stratification of disease, patients and diagnoses, and also deal with the ongoing changes in our understanding that take place over time.
Systems and Critical Thinking
.
Models, Data, Root Cause Issues
.
Disease and Patient Stratification
Disease is a Process
Leadership Team
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Chief Technology Officer
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Director, Innovation and Real World Data
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Director, Data Science & Machine Learning Engineer
Director, Data Science & Machine Learning Engineer
Chief Scientific Strategy Officer, Managing Director and Co-Founder
Director, Data Science & Machine Learning Engineer
Women's Health Advisors
Collaborators
Morehouse School of Medicine
The Wayne State University School of Medicine
Morehouse School of Medicine
Children's National Hospital
The Wayne State University School of Medicine
Morehouse School of Medicine
Nemours Children's Hospital
The Wayne State University School of Medicine
The Wayne State University School of Medicine
The Wayne State University School of Medicine
The Wayne State University School of Medicine
The Wayne State University School of Medicine
The University of California, San Diego School of Medicine
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
Penn State Health Milton S. Hershey Medical Center
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
The National Research Council (Italian: Consiglio Nazionale delle Ricerche, CNR)
The National Research Council (Italian: Consiglio Nazionale delle Ricerche, CNR)
The Global Alliance to Prevent Prematurity and Stillbirth, an initiative of Seattle Children's (GAPPS)
The National Research Council (Italian: Consiglio Nazionale delle Ricerche, CNR)
Shanghai Medical College of Fudan University
Shanghai Medical College of Fudan University
Shanghai Medical College of Fudan University
The University of Sydney
Shanghai Medical College of Fudan University
Shanghai Medical College of Fudan University
Monash University
Shanghai Medical College of Fudan University
The Norwegian Institute of Public Health
The Norwegian Institute of Public Health
Shanghai Medical College of Fudan University
The Norwegian Institute of Public Health
At IPQ: We work by redefining the problem, 'Seeing Differently' then inventing new models and tools to 'solve the problem.' we believe, 'when you can see, you can solve'
The Journey
Their collective journey extends decades of impact from: working on HER2/neu test for breast cancer, the inception of Bioinformatics, creation of bioinformatics business units into pharma, development of OWL semantic web languages, moving molecular modeling from academics to commercial opportunities, adoption of computer graphics in drug design, forefront introduction of NLP technologies for practical applications, adoption of semantic technologies (NLP and other), statin wars, industry's shift from blockbuster's in metabolic syndrome to targeted personalized medicine, digital health technologies, Affordable Care Act, concept of moving EHRs to PHRs extending office visit to patient ecosystem, commoditization of healthcare data, oncologic value based care-era......to current synthetic clinical trials and RWE to support label extensions...Along with the raw experiences of being patients in the system. These elements help inform and sculpt the unique and un-paralled approach that IPQ offers.
We came together, united by focusing on problem discovery before solution validation. Through our complementary skill sets spanning scientific, technical and commercial domains within more than 20+ diseases and conditions, we drive results going beyond addressing 'unmet clinical needs' to identify and address 'unstated, unmet clinical needs.' This requires us working closely with clinicians, patients and pharma/diagnostic groups, nationally and internationally, approaching the problem as the deep immersion into specific diseases and conditions combined with a careful abstraction to develop analytic methods and models that are disease-agnostic.
IPQ’s multi-disciplinary, leadership team, represents more than 100 years of experience in academia and industry (pharma, diagnostics, healthcare, and technology in both large corporations and startups) spanning companies such as: Abbott, Wyeth, GSK, Merck, UPenn Cancer Center, Drexel University College of Medicine, First Hospital of Wenzhou Medical University (China), University California Irvine Medical Center, American College of Healthcare Executives, Phoenix Institute of Herbal Medicine & Acupuncture, to software, real-world data vendors, health exchanges and health systems.
Advancing explainable insights since 2011
Digital Health Modeling & Analytics
Established in 2011, IPQ Analytics has been a leader in the development and application of novel solutions to healthcare and the life sciences for decades. As a digital healthcare modeling and analytics company, IPQ converts data into knowledge to extract insights from the complexities that exist within real-world healthcare. By applying proprietary Next Generation Phenotyping (NGP), IPQ enables customers with a deep understanding of the patient's clinical journey to discover new insights via private and public data. Through collaborative partnerships, novel approaches, and advanced technologies, IPQ Analytics provides the information needed for critical decision making in healthcare and life sciences.
Origin Story
Managing Director and Co-Founder, Michael Liebman, PhD, shares how IPQ Analytics LLC began in 2011
March 2023
Download PDFArchived Publications (upon request)
Community Detection in Medicine: Preserved Ejection Fraction Heart Failure (HFpEF)
Michael Liebman, * Stefania Pieroni, Michela Franchini, Loredana Fortunato, Marco Scalese, Sabrina
Molinaro, Mark Wainger, and Steven P. Reinhardt, Exploratory Research and Hypothesis in
Medicine (1-24) 2022
Application of an Automated Natural Language Processing (NLP) Workflow to Enable Federated Search
Application of an Automated Natural Language Processing (NLP) Workflow to Enable Federated Search of External Biomedical Content in Drug Discovery and Development, Robin McEntire, Debbie Szalkowski, James Butler, Michelle S. Kuo, Meiping Chang, Man Chang, Darren Freeman, Sarah McQuay, Jagruti Patel, Michael McGlashen, Wendy D. Cornell, Drug Discovery Today, May, 2016
From Personalized Medicine to Personalized Aging Services
Allen Glicksman, Misha Rodriguez, Lauren Ring, and Michael Liebman, Innovation in Aging, in press, Shifting the Paradigm, 2021
The Dress-COV Telegram Bot as a Tool for Participatory Medicine
Mi Franchini, S Pieroni, N Martini, A Ripoli, D Chiappino, F Denoth, M N Liebman, S Molinaro 1 and D Della Latta, International Journal of Environmental Research and Public Health, 17, 8786 (1-19) 2020
The Prediction of Drug-Disease Correlation based on Gene Expression Data
Cui, H., Zhang, M., Yang, Q., Li, X., Liebman, M.N., Yu, Y., and Xie L. Biomed Research International 2018
Translational Chemical Biology
Chorghade, M., Liebman, M., Lushington, G., Naylor, S. and Chaguturu, R.,Drug Discovery World, Winter 2016/2017, p72-90
Integrated Information for integrated Care in the General Practice Setting
Integrated Information for integrated Care in the General Practice Setting: Using Social Network Analysis to go
beyond the Diagnosis of Frailty in the Elderly,Franchini, M. Pieroni, S., Fortunato, L, Knezevic, T, Liebman, M.N., Molinaro, S, Clinical Translational Medicine (2016) 5:24
Poly-pharmacy among the Elderly: Analyzing the Co-morbidity of Hypertension and Diabetes
Franchini, M, Pieroni, S, Fortunato, L, Molinaro, S and Liebman, M.N, Current Pharmaceutical Design
(2015) 21(6): 791 – 805
The application of observational data in translational medicine
The application of observational data in translational medicine: analyzing tobacco-use behaviors of
adolescents Journal of Translational Medicine 2012, 10:89 doi:10.1186/1479-5876-10-89
Bridging the gap between translational medicine and unmet clinical needs
Liebman, M., Franchini, M and Molinaro, S, Technology and Health Care 23 (2015) 109–118
Drug resistance in ALK-positive Non-small cell lung cancer patients
Qian, M.. Zhu, B., Wang, X., Liebman, M. N., Seminars in Cell and Developmental Biology, (2016) in press
DW4TR: A Data Warehouse for Translational Research
Hu, H., Correll, M; Kvecher, L.; Osmond, M.; Clark, J.; Bekash, A.; Schwab, G.; Gao, D.; JGao, J.;
Kubatin;, V., Shriver, C.D.; Hooke;, J.A. Maxwell;, L.G. Kovatich, A.J., Sheldon, J.G.; Liebman,
M.N. and Mural, J Biomed Inform. 2011 Dec;44(6):1004-19. Epub 2011 Aug 22.
Volume Applications of an adaptive knowledge platform in translational medicine for breast cancer
Huttin, Christine and Michael Liebman, Technology and Healthcare, Vol 19, Number 5 (2011), pp. 349-354
Assessing semantic similarity measures for the characterization of human regulatory pathways
Guo X, Liu R, Shriver CD, Hu H, Liebman MN. Bioinformatics. 2006 Apr 15;22(8):967-73. Epub
2006 Feb 21
Expanding the perspective of translational medicine: the value of observational data
Michael N Liebman and Francesco M Marincola. Journal of Translational Medicine 2012,
10:61 doi:10.1186/1479-5876-10-61
The Economics of Biobanking and Pharmacogenetics Databasing
Huttin, C.C. and Liebman, M. N. (2013) 21, 183-190
Ultimate Question
Liebman, M. N., Translational Scientist, (2016) 2701-2705
Approaches in rare diseases and pediatrics across international boundaries
Michael Liebman, Journal of Translational Medicine 2012, 10(Suppl 2):A43 doi:10.1186/1479-5876-10-S2-A43
Technologic Innovations that will Improve Quality of Care and Quality of Life for the Cancer Patient
Lester, D and Liebman,M. N., Coping with Cancer, Lea K Jacobs, ed, Nova Science, New York, NY 2008
Hypothesis Generation and Evaluation in Clinical Trial Design
Liebman, M. N. and Molinaro, S, IEEE Transactions on Bioinformatics and Biomedicine (BIBM) Nov. 2011 p645 – 651
Bridging the Gap Between Preclinical and Clinical Informatics via Processes
Bridging the Gap Between Preclinical and Clinical Informatics via Processes, Communication and Improved Utilization of Data, at CBI’s Hepatotoxicity Summit, Nov 6-7, 2009, Philadelphia, PA
Semantic Web in the Pharmaceutical Industry
Invited presentation at Knowledge-Based Bioinformatics Workshop, Montreal, Canada, Sept 21-23, 2005
Book Chapter: “Ontologies”
In Silico Technology in Drug Target Identification and Validation, Eds. Dr. Darryl Leon and Dr. Scott Markel
myGrid and the Drug Discovery Process
Robert Stevens, Robin McEntire, Carole Goble, Mark Greenwood, Jun Zhao, Anil Wipat and Peter Li, BioSilico, May, 2004
An Evaluation of Ontology Exchange Languages for Bioinformatics
R. McEntire, Peter Karp, Neil Abernethy, David Benton, Gregg Helt, Matt DeJongh, Robert Kent, Anthony Kosky, Suzanna Lewis, Dan Hodnett, Eric Neumann, Frank Olken, Dhiraj Pathak, Peter Tarczy-Hornoch, Luca Toldo and Thodoros Topaloglou, An Evaluation of Ontology Exchange Languages for Bioinformatics, in "Proceedings Eighth International Conference on Intelligent Systems for Molecular Biology", The AAAI Press, Menlo Park, CA, USA, August, 2000
KQML - A Language and Protocol for Knowledge and Information Exchange
Tim Finin, Don McKay, Rich Fritzson, and Robin McEntire, in "Proceedings of the 13th International Distributed Artificial Intelligence Workshop", AAAI Press, July 1994
KQML: An Information and Knowledge Exchange Protocol
Tim Finin, Don McKay, Rich Fritzson, and Robin McEntire, in Toshio Yokoi (Ed.) Building and Sharing of Very Large-Scale Knowledge Bases, Ohmsha and IOS Press, 1994
Contact
Email angela@ipqanalytics.com for publications and more information
Copyright © 2011 IPQ Analytics - All Rights Reserved. Website Designed + Built by: Angela Arhontes
This website uses cookies.
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.