Prof. Elizabeth de Lange has been trained as a chemist, with a specialization in Biophysical Chemistry (Groningen University, The Netherlands). She obtained her PhD in Pharmacology (Leiden Academic Center for Drug Research (LACDR), Leiden University, The Netherlands). She currently is the Principal Investigator on Predictive Pharmacology in the Division of Systems Pharmacology & Pharmacy at the LACDR. Her aim is to adequately predict human drug effects using predictive pharmacological (translational) approaches.

More information about Elizabeth (Liesbeth) de Lange

Curriculum Vitae

Prof. Elizabeth de Lange (PhD, PharmDhc) is staff member at the Division of Systems Pharmacology & Pharmacy of the Leiden Academic Center for Drug Research (LACDR). She has been trained as a Biophysical Chemist and had her PhD in Pharmacology on “The use of microdialysis to study drug transport across the blood-brain barrier in health and disease”. 

Liesbeth’s ultimate aim is to predict human drug effects and early neurodegenerative disease stage by translational model development on the basis of preclinical and clinical data. To that end she underscores that the rate and extent of the body (biological systems) processes are condition dependent. Therefore, the mutual coherence and time dependencies of biological systems processes should be unraveled by strategic preclinical and clinical experimentation to obtain multilevel and longitudinal data combined with mathematical modelling (Mastermind Research Approach).

As the pharmacokinetics (PK) and pharmacodynamics (PD) of a drug are dependent on the interaction of the drug with the biological system, it depends on drug properties and rate and extent of biological systems processes. It is actually the understanding of the differences in the rate and extent of those processes between biological systems that forms the basis for interspecies and condition translation and prediction. Her research focusses on measurement of the PK of the drug in plasma; drug transport into and out of the target tissue; drug distribution within the target tissue; drug equilibration to the target site; and the ability of the drug to interact with the target, and (biomarkers of) the drug’s PD. These are interdependent. Particular emphasis lies on investigations on drug distribution to target tissues protected by special barriers, like the brain. A recent success has been the development of a physiologically-based multi-CNS compartment model that adequately predicts the PK of drugs in the different compartments of the mouse, rat and human CNS, only using the physico-chemical and biological properties of the drug.

As neurodegenerative diseases develop over time. For Alzheimer’s disease there is a lack of understanding on what makes the systems processes change in the onset of the disease, and how processes interact in disease progression. Especially the information on what causes the onset and early disease progression is important for developing intervening drugs before irreversible changes will dominate, to halt or even reverse the disease progression. Also here, the Mastermind Research Approach is applied, by measuring different endogenous compounds at different locations in preclinical species (including blood, Brain sites, CSF etc), at different stages in life. This will be translated to the human situation, and lay the foundation for a blood derived biomarker fingerprint, which is more patient friendly manner of a diagnose compared to a lumbar puncture for measuring in the cerebrospinal fluid (CSF), or (expensive) imaging modalities. Especially, a blood derived biomarker fingerprint of early stage AD would be of added value.

Liesbeth currently supervises the following PhD students and Postdocs:

• Berfin Gulave - PhD student
• Divakar Budda - PhD student
• Chunyuan Yin - PhD student
• Mengxu Zhang - PhD student
• Ming Sun - PhD student
• Daan van Valkgengoed - PhD student

Research Technicians:

• Dirk-Jan van den Berg
• Geert van der Horst

An overview of research projects at the Predictive Pharmacology group.

• Prediction of human (CNS) target site concentrations in health and disease
• Predicting early Alzheimer’s disease stage in human
• Drug-target binding kinetics in vivo
• Spatial (3D) CNS drug distribution model
• Prediction of human gut (colon cancer) target site concentrations and PKPD relationships
• Pharmacometabolomics; prediction of system-wide multi-biomarker drug response.

• blood-brain barrier and blood-CSF-barrier transport
• intracerebral distribution
• role of transporters in (CNS) drug pharmacokinetics
• application of population mechanism-based PK and PKPD modeling
• development of physiologically based (PB) PKPD models
• drug target binding kinetics models
• translational approaches
• prediction of drug effects
• in vitro-in vivo correlations
• theoretical studies, simulations, modeling
• neurodegeneration – Alzheimer’s disease, Parkinson’s disease
• biomarkers (drug effects, disease)
• disease progression
• prediction of disease stage
• early disease biomarker fingerprints
• application and improvement of quantitative technologies

Key Publications:

• _{Saleh M.A.A.E.W. & Lange E.C.M. de (2021), Impact of CNS diseases on drug delivery to brain extracellular and intracellular target sites in human: a “WHAT-IF” Simulation Study, Pharmaceutics 13(1): 95.}

• _{Qin T, Prins S, Groeneveld GJ, Van Westen G, de Vries HE, Wong YC, Bischoff LJM, de Lange ECM. Utility of Animal Models to Understand Human Alzheimer's Disease, Using the Mastermind Research Approach to Avoid Unnecessary Further Sacrifices of Animals. Int J Mol Sci. 2020 Apr 30;21(9). pii: E3158. doi: 10.3390/ijms21093158}

• _{Brink W.J. van den, Hartman R., Berg D.J. van den, Flik G., Gonzalez-Amoros B, Koopman N., Elassais-Schaap J., Graaf P.H. van der, Hankemeier T. & Lange E.C.M. de (2019), Blood- Based Biomarkers of Quinpirole Pharmacology: Cluster- Based PK/PD and Metabolomics to Unravel the Underlying Dynamics in Rat Plasma and Brain, CPT: Pharmacometrics & Systems Pharmacology 8(2): 107-117}

• _{Witte W.E.A. de, Danhof M., Graaf P.H. van der & Lange E.C.M. de (2019), The implications of target saturation for the use of drug-target residence time, Nature Reviews Drug Discovery 18(1): 82-84}

• _{Yamamoto Y., Välitalo P.A., Wong Y.C., Huntjens D.R., Proost J.H., Vermeulen A., Krauwinkel W., Beukers M.W., Kokki H., Kokki M., Danhof M., van Hasselt J.G.C., de Lange E.C.M., Prediction of human CNS pharmacokinetics using a physiologically-based pharmacokinetic modeling approach. Eur J Pharm Sci. 2018; 112: 168-179.}

• _{Vlot A.H.C., Witte W.E.A., Danhof M., van der Graaf P.H., van Westen G.J.P., de Lange E.C.M., Target and tissue selectivity prediction by integrated mechanistic pharmacokinetic-target binding and quantitative structure activity modelling AAPSJ. 2017; 20(1): 11.}

• _{De Lange E.C.M., van der Brink W., Yamamoto Y., de Witte W., Wong Y.C., Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics. Expert Opin Drug Discov. 2017;12(12): 1207-1218.}

• _{Brink W.J. van den, Elassais-Schaap J., Gonzalez B., Harms A., van der Graaf P.H., Hankemeier T., de Lange E.C.M., Remoxipride causes multiple pharmacokinetic/pharmacodynamic response patterns in pharmacometabolomics in rats. Eur J Pharm Sci. 2017;109: 431-440.}

• _{De Witte W., Danhof M., van der Graaf P.H., de Lange E.C., In vivo Target Residence Time and Kinetic Selectivity: The Association Rate Constant as Determinant. Trends Pharmacol Sci. 2016; 37(10): 831-42.}

• _{Stevens J., Ploeger B., Hammarlund-Udenaes M., Osswald G., van der Graaf P.H., Danhof M., de Lange E.C.M., Mechanism-based PK-PD model for the prolactin biological system response following an acute dopamine inhibition challenge: quantitative extrapolation to humans. J Pharmacokinet Pharmacodyn 2012 39(5): 463-77.}

Publications

Activities