2022 - Ljubljana - Slovenia

PAGE 2022: Drug/Disease Modelling - Other Topics
Viktor Rognås

An integrated semi-mechanistic model to predict the outcome of drug-target effects on the erythropoietic system

Viktor Rognås (1), Franziska Schaedeli Stark (1), Maddalena Marchesi (1), Hanna Silber Baumann (1), João A. Abrantes (1)

(1) Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland

Introduction: Target-related effects of investigational drugs may lead to clinical efficacy but also to safety concerns, if the target is also expressed elsewhere than intended.  Bitopertin (BTP) is a specific inhibitor of the glycine type 1 transporter (GlyT1), a transporter known to control extracellular levels of the neurotransmitter glycine in the brain, and was initially intended to be developed for psychiatric indications. The GlyT1 transporter is also expressed on erythroid cells and its inhibition leads to a decreased haemoglobin (Hb) synthesis within erythrocyte precursors due to reduced availability of glycine for the heme synthesis. As a consequence, reticulocytes (RET) with reduced Hb content are released to the blood, and Hb blood concentrations gradually decrease with a delay corresponding to the red blood cell (RBC) lifespan. Homeostatic feedback stimulates the production of new RBCs to compensate for the decreased Hb concentrations.

Objectives: To expand a previously developed semi-mechanistic model of erythropoiesis and to predict the downstream outcome of hypothetical drug-target interactions on different stages of erythropoiesis and Hb production.

Methods: Haematological biomarker data were available from 62 healthy participants in a safety and tolerability study with 120 days oral administration of 10, 30, or 60 mg of BTP or placebo QD, and 120 days follow-up. A model was previously developed based on these data to predict the risk of anaemia under long-term BTP treatment [1]. This model served as the starting point to build a more generalised erythropoiesis model by including erythroid precursors (unobserved), immature and mature RET, and an updated Hb-driven homeostatic feedback. The model was fitted simultaneously to cell count data (RBC, RET, and immature reticulocyte fraction [IRF]), as well as mean corpuscular Hb (MCH), ensuring that the system was at steady-state in the absence of a drug effect. The inhibitory effect of BTP on Hb synthesis was driven by individual AUCss. The framework was used to simulate the effect that hypothetical compounds would have when interacting with specific pathways of the erythropoiesis system. Non-linear mixed-effects modelling was used in NONMEM 7.4.3, and facilitated by PsN 4.9.3 in Improve 2.5.1-5.

Results: The final model structure consisted of a transit-compartment structure describing: (i) the formation of erythroid precursors in the bone marrow, (ii) the progression of precursors into immature and mature RET and release into the blood depending on the IRF (as implemented by Thorsted et al. [2]), (iii) the maturation of RET to RBC in blood, and (iv) the dynamics of RBC in blood. In addition, a parallel chain representing the Hb content inside the RBC was kept in the model. The estimated parameters are in agreement with the known cell lifespans, with estimated typical lifespans of 125 days for RBC and 1.2 days for RET in blood. An updated feedback mechanism to compensate for decreased Hb concentrations in the blood was supported by the data through: (i) stimulation of precursor cell production, and (ii) more efficient release of RET from the bone marrow into the blood. The predictive performance of this expanded model proved adequate for all measured biomarkers. Simulations of hypothetical drug-target effects on the production or transit rates of different types of RBC precursors illustrated that the schedule and duration of drug exposure may be key elements to control the extent of downstream effects in the blood potentially leading to anaemia.

Conclusions: An integrated semi-mechanistic population PKPD model, taking into account the turnover of cells and haemoglobin-driven feedback mechanisms, was used to describe the process of erythropoiesis.  By including RBC precursor cells, the model can translate short term effects observed in RET into more delayed downstream effects on Hb and RBC. The updated model, complementing other models [2], leverages the data from a previously conducted long-term haematologic study and supports the development of new compounds with a potential effect on erythropoiesis.



References:
[1] Schaedeli Stark F, Martin-Facklam M, Hofmann C, Boutouyrie B, Cosson V. Semi-physiologic population PKPD model characterizing the effect of bitopertin (RG1678) glycine reuptake inhibitor on hemoglobin turnover in humans. PAGE 21 Abstr 2553, 2012.
[2] Thorsted A, Zecchin C, Berges A, Karlsson MO, Friberg LE. An integrated model for red blood cells, reticulocytes, hemoglobin, platelets, erythropoietin, and thrombopoietin. ACoP12, 2021.


Reference: PAGE 30 (2022) Abstr 10044 [www.page-meeting.org/?abstract=10044]
Poster: Drug/Disease Modelling - Other Topics
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