Minimal brain PBPK model to support the preclinical and clinical development of antibody therapeutics for CNS diseases.

There are several antibody therapeutics in preclinical and clinical development, industry-wide, for the treatment of central nervous system (CNS) disorders. Due to the limited permeability of antibodies across brain barriers, the quantitative understanding of antibody exposure in the CNS is important for the design of antibody drug characteristics and determining appropriate dosing regimens. We have developed a minimal physiologically-based pharmacokinetic (mPBPK) model of the brain for antibody therapeutics, which was reduced from an existing multi-species platform brain PBPK model. All non-brain compartments were combined into a single tissue compartment and cerebral spinal fluid (CSF) compartments were combined into a single CSF compartment. The mPBPK model contains 16 differential equations, compared to 100 in the original PBPK model, and improved simulation speed approximately 11-fold. Area under the curve ratios for minimal versus full PBPK models were close to 1 across species for both brain and plasma compartments, which indicates the reduced model simulations are similar to those of the original model. The minimal model retained detailed physiological processes of the brain while not significantly affecting model predictability, which supports the law of parsimony in the context of balancing model complexity with added predictive power. The minimal model has a variety of applications for supporting the preclinical development of antibody therapeutics and can be expanded to include target information for evaluating target engagement to inform clinical dose selection.

Extending a Systems Model of the APP Pathway: Separation of ß- and γ-Secretase Sequential Cleavage Steps of APP.

The abnormal accumulation of amyloid-ß (Aß) in the brain parenchyma has been posited as a central event in the pathophysiology of Alzheimer's disease. Recently, we have proposed a systems pharmacology model of the amyloid precursor protein (APP) pathway, describing the Aß APP metabolite responses (Aß40, Aß42, sAPPα, and sAPPß) to ß-secretase 1 (BACE1) inhibition. In this investigation this model was challenged to describe Aß dynamics following γ-secretase (GS) inhibition. This led an extended systems pharmacology model, with separate descriptions to characterize the sequential cleavage steps of APP by BACE1 and GS, to describe the differences in Aß response to their respective inhibition. Following GS inhibition, a lower Aß40 formation rate constant was observed, compared with BACE1 inhibition. Both BACE1 and GS inhibition were predicted to lower Aß oligomer levels. Further model refinement and new data may be helpful to fully understand the difference in Aß dynamics following BACE1 versus GS inhibition.

Systems Pharmacology Analysis of the Amyloid Cascade after ß-Secretase Inhibition Enables the Identification of an Aß42 Oligomer Pool.

The deposition of amyloid-ß (Aß) oligomers in brain parenchyma has been implicated in the pathophysiology of Alzheimer's disease. Here we present a systems pharmacology model describing the changes in the amyloid precursor protein (APP) pathway after administration of three different doses (10, 30, and 125 mg/kg) of the ß-secretase 1 (BACE1) inhibitor MBi-5 in cisterna magna ported rhesus monkeys. The time course of the MBi-5 concentration in plasma and cerebrospinal fluid (CSF) was analyzed in conjunction with the effect on the concentrations of the APP metabolites Aß42, Aß40, soluble ß-amyloid precursor protein (sAPP) α, and sAPPß in CSF. The systems pharmacology model contained expressions to describe the production, elimination, and brain-to-CSF transport for the APP metabolites. Upon administration of MBi-5, a dose-dependent increase of the metabolite sAPPα and dose-dependent decreases of sAPPß and Aß were observed. Maximal inhibition of BACE1 was close to 100% and the IC50 value was 0.0256 µM (95% confidence interval, 0.0137-0.0375). A differential effect of BACE1 inhibition on Aß40 and Aß42 was observed, with the Aß40 response being larger than the Aß42 response. This enabled the identification of an Aß42 oligomer pool in the systems pharmacology model. These findings indicate that decreases in monomeric Aß responses resulting from BACE1 inhibition are partially compensated by dissociation of Aß oligomers and suggest that BACE1 inhibition may also reduce the putatively neurotoxic oligomer pool.