Therapeutic Areas

qPharmetra has completed multiple projects in all these therapeutic areas. The firm has particularly deep experience with oncology, CNS and Cardiovascular drugs, resulting in models with nuanced insights on mechanisms and biology.

Oncology CNS Cardiovascular
Endocrinology Infectious Disease Pain
Gastrointestinal Men’s Health Rare Disease
Hematology Metabolic Disease Respiratory
Immunology Musculoskeletal Urology

All Phases of Drug Development

qPharmetra’s skills can be used at all stages of drug development from preclinical through Phase 4 to make better decisions that lead to better medicines. Establishing models early in the drug development process helps to define the assumptions around a drug, define areas where data are needed and provide a structure for integrating diverse datasets.

Regulatory Interactions

qPharmetra regularly works with its clients to produce or support regulatory documents that help to clearly express the insights from their data to justify doses, support approval, and demonstrate risks and benefits of the drug. qPharmetra has helped produce more than a dozen NDA/CTD submissions.

Industry Experience

qPharmetra consultants average over 15 years of industry experience working directly in pharma companies and consulting for them. This depth of experience allows them to understand both the technical and organizational challenges in drug development.


Most of the qPharmetra consultants are scientists or engineers with PhDs in chemical engineering, pharmaceutical science and biomathematics. This provides a range of perspectives to help solve challenging problems.


qPharmetra is comitted to sharing knowledge that will assist others in developing better medicines. To accomplish this, we publish our work whenever a client agrees, so that the drug development community and ultimately patients will benefit from new information about a drug or disease. Here are the recent publications from the qP team:

  • Journal Articles
  • Dykstra K, Mehrotra N, Tornøe C, Kastrissios H, Patel B, Al-Huniti N, Jadhav P, Wang Y, Byon W, Reporting guidelines for population pharmacokinetic analyses, J Pharmacokinet Pharmacodyn, 2015, 42, 301-314. Also J Clin Pharmacol, in press.
  • Borin M, Chen M, Mocci S, Rubets I, Chittenden J, Aldairy W, Stroh M, Onartuzumab with or without bevacizumab in combination with weekly paclitaxel does not prolong QTc or adversely affect other ECG parameters in patients with locally recurrent or metastatic triple-negative breast cancer,  Cancer Chemotherapy and Pharmacology, 2015, 75, 401-410.
  • Rharbaoui F, Prins NH,  Holzkämper T, Petersson K, Czeloth N, Kaiser S, König M, Wartenberg-Demand A, Engling A, Gutscher M, Wolter R, Abufarag A, Aigner S, Dälken B, Modeling of the relationship between dose and biomarker response of the anti-CD4 monoclonal antibody tregalizumab for the treatment of rheumatoid arthritis. JCPT 2015 submitted.
  • Xu Y, Prohn M, Cai X, Crutchlow M, Shankar SS, Bateman K, Woolf EJ, Direct comparison of radioimmunoassay and LC-MS/MS for PK assessment of insulin glargine in clinical development, Bioanalysis. 2014 Dec; 6(24):3311-23. doi: 10.4155/bio.14.219.
  • Kesisoglou F, Rossenu S, Farrell C, Van Den Heuvel M, Prohn M, Fitzpatrick S, De Kam PJ, Vargo R, Development of in vitro-in vivo correlation for extended-release niacin after administration of hypromellose-based matrix formulations to healthy volunteers, J Pharm Sci. 2014 Nov; 103(11):3713-23. doi: 10.1002/jps.24179. Epub 2014 Sep 24.
  • Chittenden J, Brooks J, Riviere J, Development of a Mixed-Effect Pharmacokinetic Model for Vehicle Modulated In Vitro Transdermal Flux of Topically Applied Penetrants, J. Pharm. Sci., 2014, 103, 1002-1012
  • Boström E, Öhrn F, Hanze E, Sandström M, Martin P, Wählby‐Hamrén U, Exposure vs. response of blood pressure in patients with rheumatoid arthritis following treatment with fostamatinib, The Journal of Clinical Pharmacology, 2014 54(12), 1337-1346.
  • De Kam PJ, Grobara P, Prohn M, Höppener F, Kluft C, Burggraaf J, Langdon RB, Peeters P, Effects of sugammadex on activated partial thromboplastin time and prothrombin time in healthy subjects,  Int J Clin Pharmacol Ther. 2014 Mar; 52(3):227-36. doi: 10.5414/CP201976.
  • Viberg A, Martino G, Lessard E, Laird JM. Evaluation of an innovative population pharmacokinetic-based design for behavioral pharmacodynamic endpoints. AAPS J. 2012 Dec;14(4):657-63.
  • Abstracts and Presentations
  • Chittenden J, Prins NH, Evaluation of stepwise covariate model selection using Bayesian models. Poster PAGE meeting 2015.
  • Viberg A, Petersson K, Hoeben E, Brochot A, A Population PK Model for Simeprevir in Healthy Volunteers and Patients, PAGE meeting 2015, Abstr 3368 []
  • Reddy VP, Ruston L, Grant I, Wilkinson G, Davies B, Williams L, Ellston R, Hilgendorf C, Lindbom L, Brogren J, Jones R, Pease E, Modelling and simulation of concentration-depth-time profiles in the urinary bladder wall following intravesical delivery, PAGE meeting 2015, Abstr 3360
  • Prins K, Acknowledging dispersion increases the power to detect central tendencies in underdispersed count data models at low treatment arm size, Poster PAGE meeting 2015.
  • Burroughs E, Valiathan C,Dykstra K, Cho C, Immuno-Viral Dynamics Modeling of Letermovir for Treatment and Prophylaxis Indication of Human Cytomegalovirus (HCMV) Infection in Post-Transplant Settings, ACoP 6 (2015).