Berfin Gülave (1), Mohammed A.A. Saleh (1), J.G. Coen van Hasselt (1), Elizabeth C.M. de Lange (1)
(1) Research division of Systems Biomedicine and Pharmacology, LACDR, Leiden University, the Netherlands
Objectives: Chronic pain is an undesirable condition with drug treatments being mainly ineffective and are often associated with adverse effects. For adequate treatment, the underlying relationship between unbound drug exposure at the central nervous system (CNS) target site, target site binding kinetics, and drug effects needs to be characterized. Research is needed on local CNS drug (target site) exposure in chronic pain as unbound drug exposure in the CNS may differ substantially from that in plasma, and between different parts of the CNS, while also may be influenced by chronic pain. Since direct measurement of unbound drug concentrations in the human CNS is highly limited due to ethical constraints. Physiologically-based (PB) pharmacokinetic (PK) models can be used to predict CNS drug exposure, as previously described in the LeiCNS-PK3.0 model for a variety of drugs [1]. The use of these PBPK models further allows investigation of specific physiological changes associated with chronic pain that may affect CNS drug exposure. We aim to further develop the LeiCNS-PK3.0 model to predict human CNS distribution of multiple analgesic drugs, in healthy subjects and chronic pain patients. Here, we study the influence of pathophysiological changes in blood-brain-barrier (BBB) transport modes are studied for the commonly used opioids as diminished analgesic effects of opioids have been reported under pain conditions [2-4].
Methods: Physiological (system-specific), drug-specific, plasma PK and BBB transport related parameters were collected from literature and databases. The collected data was used in the model to predict CNS (brain extracellular, ECF, and intracellular fluid, ICF) distribution for codeine, hydrocodone, morphine and oxycodone under healthy and pain-related condition. For the latter condition, parameters related to passive transport, effective surface area for passive transport, and active BBB efflux by P-glycoprotein (P-gp) are increased as has been reported for pain-related conditions [2,3]. The CNS predictions of these opioids were based on the standard oral dosing and multiple administrations.
Results: The concentration time profile of morphine with an increased passive and active BBB efflux transport showed an average net decrease exposure of 6% at the CNS target site (brain ECF) compared to healthy condition. Hydrocodone, not a substrate for the active efflux transporter P-gp, showed an average increase of 6% in CNS target site exposure after every administration. Whereas codeine, known to be only passively transported, and oxycodone, known to be actively transported into the CNS, shows only a minor higher exposure after the first administrations and equal exposure with further administrations.
Conclusion: The net decreased morphine exposure at the target site is in line with the reduced effectiveness of morphine in pain conditions, compared to a normal situation. Hydrocodone is not a substrate for P-gp [5], for this reason, the increased exposure may suggest that hydrocodone mainly follows passively transport across BBB. However, the increase in passive and active BBB efflux seems not to significantly affect the target site exposure of codeine and oxycodone, suggesting these drugs not directly being involved in the two adjusted transport modes. Nevertheless, pain is multifactorial and complex, and more factors in CNS opioid distribution needs to be considered.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 848068 (www.QSPainRelief.eu).
References
[1] Saleh MAA et al. J Pharmacokinet Pharmacodyn (2021), Submitted.
[2] Seelbach MJ et al. J Neurochem (2007) 102(5), 1677-1690
[3] Hau VS et al. Brain Res (2004) 1018(2), 257-264
[4] Ballantyne JC et al. N Engl J Med (2003) 349(20), 1943-1953
[5] Yang J et al, Pharmaceutics (2018) 10(4), 192
Reference: PAGE 29 (2021) Abstr 9609 [www.page-meeting.org/?abstract=9609]
Poster: Drug/Disease Modelling - CNS