Kapil Gadkar

Therapeutic bispecific antibodies cross the blood-brain barrier in nonhuman primates

Bispecific antibodies engineered to both bind to the primate transferrin receptor and inhibit β-secretase are taken up by the nonhuman primate brain and reduce brain β-amyloid. A Two-Pronged Approach for Central Nervous System Therapeutics The brain has been considered off-limits to antibody therapies because of the blood-brain barrier (BBB), which protects the brain from circulating toxins while selectively transporting essential molecules into the brain. Efforts to use natural transport mechanisms to deliver antibody therapies into the brain have been successful in rodents. Whether a similar approach can be used in primates, including humans, remains unknown. Using bispecific antibodies with one arm binding to the transferrin receptor and the other to an Alzheimer’s disease drug target, we show that therapeutic antibodies can effectively and safely cross the BBB and enter the primate brain, thus paving the way for antibody therapeutics to treat central nervous system diseases in humans. Using therapeutic antibodies that need to cross the blood-brain barrier (BBB) to treat neurological disease is a difficult challenge. We have shown that bispecific antibodies with optimized binding to the transferrin receptor (TfR) that target β-secretase (BACE1) can cross the BBB and reduce brain amyloid-β (Aβ) in mice. Can TfR enhance antibody uptake in the primate brain? We describe two humanized TfR/BACE1 bispecific antibody variants. Using a human TfR knock-in mouse, we observed that anti-TfR/BACE1 antibodies could cross the BBB and reduce brain Aβ in a TfR affinity–dependent fashion. Intravenous dosing of monkeys with anti-TfR/BACE1 antibodies also reduced Aβ both in cerebral spinal fluid and in brain tissue, and the degree of reduction correlated with the brain concentration of anti-TfR/BACE1 antibody. These results demonstrate that the TfR bispecific antibody platform can robustly and safely deliver therapeutic antibody across the BBB in the primate brain.

Addressing safety liabilities of TfR bispecific antibodies that cross the blood-brain barrier.

The safety of therapeutic bispecific antibodies that use TfR for delivery to the brain can be improved by reducing affinity for TfR and eliminating antibody effector function. Averting Roadblocks En Route to the Brain The blood-brain barrier represents a formidable blockade preventing therapeutic antibody delivery into the brain. Bispecific antibodies using the transferrin receptor (TfR) have shown promise for boosting therapeutic antibody uptake into the brain. Although TfR can act as a molecular lift to promote brain uptake, little is known about the safety ramifications of this approach. Building on a pair of studies published in Science Translational Medicine, Couch and colleagues now report that when mice were dosed with therapeutic TfR antibodies, the animals showed acute clinical reactions and a reduction in immature red blood cells, known as reticulocytes. TfR bispecific antibodies engineered to lack Fc interactions with immune cells eliminated adverse acute clinical reactions and reduced reticulocyte loss; the extent of reticulocyte loss was also influenced by binding to TfR and interaction with the complement cascade. Because reticulocytes express high levels of TfR, other cell types that express high levels of TfR were also investigated. The authors observed, for example, that the blood-brain barrier remained completely intact after TfR antibodies were administered to mice, despite the high expression of TfR in brain endothelial cells. Finally, multiple doses of TfR/BACE1 bispecific antibodies reduced amyloid-β, a toxic protein implicated in Alzheimer’s disease, with minimal sustained toxicity. Investigation of monkey and human TfR levels in circulating reticulocytes suggested that loss of these cells may be less likely to occur in primates than in mice. The translational implications of these discoveries suggest that the blood-brain barrier is not the only obstacle to surmount on the way to the brain, at least when using TfR as a molecular lift. Bispecific antibodies using the transferrin receptor (TfR) have shown promise for boosting antibody uptake in brain. Nevertheless, there are limited data on the therapeutic properties including safety liabilities that will enable successful development of TfR-based therapeutics. We evaluate TfR/BACE1 bispecific antibody variants in mouse and show that reducing TfR binding affinity improves not only brain uptake but also peripheral exposure and the safety profile of these antibodies. We identify and seek to address liabilities of targeting TfR with antibodies, namely, acute clinical signs and decreased circulating reticulocytes observed after dosing. By eliminating Fc effector function, we ameliorated the acute clinical signs and partially rescued a reduction in reticulocytes. Furthermore, we show that complement mediates a residual decrease in reticulocytes observed after Fc effector function is eliminated. These data raise important safety concerns and potential mitigation strategies for the development of TfR-based therapies that are designed to cross the blood-brain barrier.

The Type 1 Diabetes PhysioLab® Platform: a validated physiologically based mathematical model of pathogenesis in the non‐obese diabetic mouse

Type 1 diabetes is an autoimmune disease whose clinical onset signifies a lifelong requirement for insulin therapy and increased risk of medical complications. To increase the efficiency and confidence with which drug candidates advance to human type 1 diabetes clinical trials, we have generated and validated a mathematical model of type 1 diabetes pathophysiology in a well‐characterized animal model of spontaneous type 1 diabetes, the non‐obese diabetic (NOD) mouse. The model is based on an extensive survey of the public literature and input from an independent scientific advisory board. It reproduces key disease features including activation and expansion of autoreactive lymphocytes in the pancreatic lymph nodes (PLNs), islet infiltration and β cell loss leading to hyperglycaemia. The model uses ordinary differential and algebraic equations to represent the pancreas and PLN as well as dynamic interactions of multiple cell types (e.g. dendritic cells, macrophages, CD4+ T lymphocytes, CD8+ T lymphocytes, regulatory T cells, β cells). The simulated features of untreated pathogenesis and disease outcomes for multiple interventions compare favourably with published experimental data. Thus, a mathematical model reproducing type 1 diabetes pathophysiology in the NOD mouse, validated based on accurate reproduction of results from multiple published interventions, is available for in silico hypothesis testing. Predictive biosimulation research evaluating therapeutic strategies and underlying biological mechanisms is intended to deprioritize hypotheses that impact disease outcome weakly and focus experimental research on hypotheses likely to provide insight into the disease and its treatment.

Mechanism-Based Pharmacokinetic/Pharmacodynamic Model for THIOMAB™ Drug Conjugates

ABSTRACTPurposeTHIOMAB™ drug conjugates (TDCs) with engineered cysteine residues allow site-specific drug conjugation and defined Drug-to-Antibody Ratios (DAR). In order to help elucidate the impact of drug-loading, conjugation site, and subsequent deconjugation on pharmacokinetics and efficacy, we have developed an integrated mathematical model to mechanistically characterize pharmacokinetic behavior and preclinical efficacy of MMAE conjugated TDCs with different DARs. General applicability of the model structure was evaluated with two different TDCs.MethodPharmacokinetics studies were conducted for unconjugated antibody and purified TDCs with DAR-1, 2 and 4 for trastuzumab TDC and Anti-STEAP1 TDC in mice. Total antibody concentrations and individual DAR fractions were measured. Efficacy studies were performed in tumor-bearing mice.ResultsAn integrated model consisting of distinct DAR species (DAR0-4), each described by a two-compartment model was able to capture the experimental data well. Time series measurements of each Individual DAR species allowed for the incorporation of site-specific drug loss through deconjugation and the results suggest a higher deconjugation rate from heavy chain site HC-A114C than the light chain site LC-V205C. Total antibody concentrations showed multi-exponential decline, with a higher clearance associated with higher DAR species. The experimentally observed effects of TDC on tumor growth kinetics were successfully described by linking pharmacokinetic profiles to DAR-dependent killing of tumor cells.ConclusionResults from the integrated model evaluated with two different TDCs highlight the impact of DAR and site of conjugation on pharmacokinetics and efficacy. The model can be used to guide future drug optimization and in-vivo studies.

A Mechanistic Systems Pharmacology Model for Prediction of LDL Cholesterol Lowering by PCSK9 Antagonism in Human Dyslipidemic Populations

PCSK9 is a promising target for the treatment of hyperlipidemia and cardiovascular disease. A Quantitative Systems Pharmacology model of the mechanisms of action of statin and anti-PCSK9 therapies was developed to predict low density lipoprotein (LDL) changes in response to anti-PCSK9 mAb for different treatment protocols and patient subpopulations. Mechanistic interactions and cross-regulation of LDL, LDL receptor, and PCSK9 were modeled, and numerous virtual subjects were developed and validated against clinical data. Simulations predict a slightly greater maximum percent reduction in LDL cholesterol (LDLc) when anti-PCSK9 is administered on statin background therapy compared to as a monotherapy. The difference results primarily from higher PCSK9 levels in patients on statin background. However, higher PCSK9 levels are also predicted to increase clearance of anti-PCSK9, resulting in a faster rebound of LDLc. Simulations of subjects with impaired LDL receptor (LDLR) function predict compromised anti-PCSK9 responses in patients such as homozygous familial hypercholesterolemics, whose functional LDLR is below 10% of normal. CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e149; doi:10.1038/psp.2014.47; published online 26 November 2014.PCSK9 is a promising target for the treatment of hyperlipidemia and cardiovascular disease. A Quantitative Systems Pharmacology model of the mechanisms of action of statin and anti‐PCSK9 therapies was developed to predict low density lipoprotein (LDL) changes in response to anti‐PCSK9 mAb for different treatment protocols and patient subpopulations. Mechanistic interactions and cross‐regulation of LDL, LDL receptor, and PCSK9 were modeled, and numerous virtual subjects were developed and validated against clinical data. Simulations predict a slightly greater maximum percent reduction in LDL cholesterol (LDLc) when anti‐PCSK9 is administered on statin background therapy compared to as a monotherapy. The difference results primarily from higher PCSK9 levels in patients on statin background. However, higher PCSK9 levels are also predicted to increase clearance of anti‐PCSK9, resulting in a faster rebound of LDLc. Simulations of subjects with impaired LDL receptor (LDLR) function predict compromised anti‐PCSK9 responses in patients such as homozygous familial hypercholesterolemics, whose functional LDLR is below 10% of normal.

The virtual NOD mouse: applying predictive biosimulation to research in type 1 diabetes.

Abstract:  Type 1 diabetes is a complex, multifactorial disease characterized by T cell–mediated autoimmune destruction of insulin‐secreting pancreatic β cells. To facilitate research in type 1 diabetes, a large‐scale dynamic mathematical model of the female non‐obese diabetic (NOD) mouse was developed. In this model, termed the Entelos® Type 1 Diabetes PhysioLab® platform, virtual NOD mice are constructed by mathematically representing components of the immune system and islet β cell physiology important for the pathogenesis of type 1 diabetes. This report describes the scope of the platform and illustrates some of its capabilities. Specifically, using two virtual NOD mice with either average or early diabetes‐onset times, we demonstrate the reproducibility of experimentally observed dynamics involved in diabetes progression, therapeutic responses to exogenous IL‐10, and heterogeneity in disease onset. Additionally, we use the Type 1 Diabetes PhysioLab platform to investigate the impact of disease heterogeneity on the effectiveness of exogenous IL‐10 therapy to prevent diabetes onset. Results indicate that the inability of a previously published IL‐10 therapy protocol to protect NOD mice who exhibit early diabetes onset is due to high levels of pancreatic lymph node (PLN) inflammation, islet infiltration, and β cell destruction at the time of treatment initiation. Further, simulation indicates that earlier administration of the treatment protocol can prevent NOD mice from developing diabetes by initiating treatment during the period when the disease is still sensitive to IL‐10s protective function.

Evaluation of HDL-modulating interventions for cardiovascular risk reduction using a systems pharmacology approach.

The recent failures of cholesteryl ester transport protein inhibitor drugs to decrease CVD risk, despite raising HDL cholesterol (HDL-C) levels, suggest that pharmacologic increases in HDL-C may not always reflect elevations in reverse cholesterol transport (RCT), the process by which HDL is believed to exert its beneficial effects. HDL-modulating therapies can affect HDL properties beyond total HDL-C, including particle numbers, size, and composition, and may contribute differently to RCT and CVD risk. The lack of validated easily measurable pharmacodynamic markers to link drug effects to RCT, and ultimately to CVD risk, complicates target and compound selection and evaluation. In this work, we use a systems pharmacology model to contextualize the roles of different HDL targets in cholesterol metabolism and provide quantitative links between HDL-related measurements and the associated changes in RCT rate to support target and compound evaluation in drug development. By quantifying the amount of cholesterol removed from the periphery over the short-term, our simulations show the potential for infused HDL to treat acute CVD. For the primary prevention of CVD, our analysis suggests that the induction of ApoA-I synthesis may be a more viable approach, due to the long-term increase in RCT rate.

Mathematical PKPD and safety model of bispecific TfR/BACE1 antibodies for the optimization of antibody uptake in brain

Treatment of diseases of the central nervous system by monoclonal antibodies may be limited by the restricted uptake of antibodies across the blood-brain barrier (BBB). An antibody targeting transferrin receptor (TfR) has been shown to take advantage of the receptor-mediated transcytosis properties of TfR in order to cross the BBB in mice, with the uptake in the brain being dependent on the affinity to TfR. In the bispecific format with arms targeting both TfR and β-secretase 1 (BACE1), altering the affinity to TfR has been shown to impact systemic exposure and safety profiles. In this work, a mathematical model incorporating pharmacokinetic/pharmacodynamic (PKPD) and safety profiles is developed for bispecific TfR/BACE1 antibodies with a range of affinities to TfR in order to guide candidate selection. The model captures the dependence of both systemic and brain exposure on TfR affinity and the subsequent impact on brain Aβ40 lowering and circulating reticulocyte levels. Model simulations identify the optimal affinity for the TfR arm of the bispecific to maximize Aβ reduction while maintaining reticulocyte levels. The model serves as a useful tool to prioritize and optimize preclinical studies and has been used to support the selection of additional candidates for further development.

Dosing and Timing Effects of Anti-CD40L Therapy

Abstract:  Several publications describing the use of anti‐CD40L monoclonal antibodies (anti‐CD40L) for the treatment of type 1 diabetes in non‐obese diabetic (NOD) mice have reported different treatment responses to similar protocols. The Entelos® Type 1 Diabetes PhysioLab® platform, a dynamic large‐scale mathematical model of the pathogenesis of type 1 diabetes, was used to study the effects of anti‐CD40L therapy in silico. An examination of the impact of pharmacokinetic variability and the heterogeneity of disease progression rate on therapeutic outcome provided insights that could reconcile the apparently conflicting data. Optimal treatment protocols were identified by exploring the dynamics of key pathophysiological pathways.

Quantitative systems pharmacology: a promising approach for translational pharmacology

Biopharmaceutical companies have increasingly been exploring Quantitative Systems Pharmacology (QSP) as a potential avenue to address current challenges in drug development. In this paper, we discuss the application of QSP modeling approaches to address challenges in the translational of preclinical findings to the clinic, a high risk area of drug development. Three cases have been highlighted with QSP models utilized to inform different questions in translational pharmacology. In the first, a mechanism based asthma model is used to evaluate efficacy and inform biomarker strategy for a novel bispecific antibody. In the second case study, a mitogen-activated protein kinase (MAPK) pathway signaling model is used to make translational predictions on clinical response and evaluate novel combination therapies. In the third case study, a physiologically based pharmacokinetic (PBPK) model it used to guide administration of oseltamivir in pediatric patients.