Neil Benson

Systems Pharmacology: Bridging Systems Biology and Pharmacokinetics-Pharmacodynamics (PKPD) in Drug Discovery and Development

ABSTRACTMechanistic PKPD models are now advocated not only by academic and industrial researchers, but also by regulators. A recent development in this area is based on the growing realisation that innovation could be dramatically catalysed by creating synergy at the interface between Systems Biology and PKPD, two disciplines which until now have largely existed in ‘parallel universes’ with a limited track record of impactful collaboration. This has led to the emergence of systems pharmacology. Broadly speaking, this is the quantitative analysis of the dynamic interactions between drug(s) and a biological system to understand the behaviour of the system as a whole, as opposed to the behaviour of its individual constituents; thus, it has become the interface between PKPD and systems biology. It applies the concepts of Systems Engineering, Systems Biology, and PKPD to the study of complex biological systems through iteration between computational and/or mathematical modelling and experimentation. Application of systems pharmacology can now impact across all stages of drug research and development, ranging from very early discovery programs to large-scale Phase 3/4 patient studies, and has the potential to become an integral component of a new ‘enhanced quantitative drug discovery and development’ (EQD3) R&D paradigm.

Model-based drug development: a rational approach to efficiently accelerate drug development.

The pharmaceutical industry continues to face significant challenges. Very few compounds that enter development reach the marketplace, and the investment required for each success can surpass

Bridging the gap between in silico and cell‐based analysis of the nuclear factor‐κB signaling pathway by in vitro studies of IKK2

1.8 billion. Despite attempts to improve efficiency and increase productivity, total investment continues to rise whereas the output of new medicines declines. With costs increasing exponentially through each development phase, it is failure in phase II and phase III that is most wasteful. In todays development paradigm, late‐stage failure is principally a result of insufficient efficacy. This is manifested as either a failure to differentiate sufficiently from placebo (shown for both novel and precedented mechanisms) or a failure to demonstrate sufficient differentiation from existing compounds. Set in this context, this article will discuss the role model‐based drug development (MBDD) approaches can and do play in accelerating and optimizing compound development strategies through a series of illustrative examples.

A Systems Pharmacology Perspective on the Clinical Development of Fatty Acid Amide Hydrolase Inhibitors for Pain

Previously, we have shown by sensitivity analysis, that the oscillatory behavior of nuclear factor (NF‐κB) is coupled to free IkappaB kinase‐2 (IKK2) and IkappaBalpha(IκBα), and that the phosphorylation of IκBα by IKK influences the amplitude of NF‐κB oscillations. We have performed further analyses of the behavior of NF‐κB and its signal transduction network to understand the dynamics of this system. A time lapse study of NF‐κB translocation in 10 000 cells showed discernible oscillations in levels of nuclear NF‐κB amongst cells when stimulated with interleukin (IL‐1α), which suggests a small degree of synchronization amongst the cell population. When the kinetics for the phosphorylation of IκBα by IKK were measured, we found that the values for the affinity and catalytic efficiency of IKK2 for IκBα were dependent on assay conditions. The application of these kinetic parameters in our computational model of the NF‐κB pathway resulted in significant differences in the oscillatory patterns of NF‐κB depending on the rate constant value used. Hence, interpretation of in silico models should be made in the context of this uncertainty.

Reducing Systems Biology to Practice in Pharmaceutical Company Research; Selected Case Studies

The level of the endocannabinoid anandamide is controlled by fatty acid amide hydrolase (FAAH). In 2011, PF‐04457845, an irreversible inhibitor of FAAH, was progressed to phase II clinical trials for osteoarthritic pain. This article discusses a prospective, integrated systems pharmacology model evaluation of FAAH as a target for pain in humans, using physiologically based pharmacokinetic and systems biology approaches. The model integrated physiological compartments; endocannabinoid production, degradation, and disposition data; PF‐04457845 pharmacokinetics and pharmacodynamics, and cannabinoid receptor CB1‐binding kinetics. The modeling identified clear gaps in our understanding and highlighted key risks going forward, in particular relating to whether methods are in place to demonstrate target engagement and pharmacological effect. The value of this modeling exercise will be discussed in detail and in the context of the clinical phase II data, together with recommendations to enable optimal future evaluation of FAAH inhibitors.

Impact of plasma-protein binding on receptor occupancy: An analytical description

Reviews of the productivity of the pharmaceutical industry have concluded that the current business model is unsustainable. Various remedies for this have been proposed, however, arguably these do not directly address the fundamental issue; namely, that it is the knowledge required to enable good decisions in the process of delivering a drug that is largely absent; in turn, this leads to a disconnect between our intuition of what the right drug target is and the reality of pharmacological intervention in a system such as a human disease state. As this system is highly complex, modelling will be required to elucidate emergent properties together with the data necessary to construct such models. Currently, however, both the models and data available are limited. The ultimate solution to the problem of pharmaceutical productivity may be the virtual human, however, it is likely to be many years, if at all, before this goal is realised. The current challenge is, therefore, whether systems modelling can contribute to improving productivity in the pharmaceutical industry in the interim and help to guide the optimal route to the virtual human. In this context, this chapter discusses the emergence of systems pharmacology in drug discovery from the interface of pharmacokinetic-pharmacodynamic modelling and systems biology. Examples of applications to the identification of optimal drug targets in given pathways, selecting drug modalities and defining biomarkers are discussed, together with future directions.

Systems pharmacology of the nerve growth factor pathway: use of a systems biology model for the identification of key drug targets using sensitivity analysis and the integration of physiology and pharmacology.

In this paper we analyse the dynamics of an inhibitor I which can either bind to a receptor R or to a plasma protein P. Assuming typical association and dissociation rates, we find that after an initial dose of inhibitor, there are three time scales: a short one, measured in fractions of seconds, in which the inhibitor concentration and the plasma-protein complex jump to quasi-stationary values, a medium one, measured in seconds in which the receptor complex rises to an equilibrium value and a large one, measured in hours in which the inhibitor-receptor complex slowly drops down to zero. We show that the average receptor occupancy, the pharmacologically relevant quantity, taken over, say, 24h reaches a maximal value for a specific value of the plasma-protein binding constant. Potentially, understanding and exploiting this optimum could be of great interest to those involved in drug discovery and development.

NanoStore: A Concept for Logistical Improvements of Compound Handling in High-Throughput Screening

The nerve growth factor (NGF) pathway is of great interest as a potential source of drug targets, for example in the management of certain types of pain. However, selecting targets from this pathway either by intuition or by non-contextual measures is likely to be challenging. An alternative approach is to construct a mathematical model of the system and via sensitivity analysis rank order the targets in the known pathway, with respect to an endpoint such as the diphosphorylated extracellular signal-regulated kinase concentration in the nucleus. Using the published literature, a model was created and, via sensitivity analysis, it was concluded that, after NGF itself, tropomyosin receptor kinase A (TrkA) was one of the most sensitive druggable targets. This initial model was subsequently used to develop a further model incorporating physiological and pharmacological parameters. This allowed the exploration of the characteristics required for a successful hypothetical TrkA inhibitor. Using these systems models, we were able to identify candidates for the optimal drug targets in the known pathway. These conclusions were consistent with clinical and human genetic data. We also found that incorporating appropriate physiological context was essential to drawing accurate conclusions about important parameters such as the drug dose required to give pathway inhibition. Furthermore, the importance of the concentration of key reactants such as TrkA kinase means that appropriate contextual data are required before clear conclusions can be drawn. Such models could be of great utility in selecting optimal targets and in the clinical evaluation of novel drugs.

Design and optimisation of orally active TLR7 agonists for the treatment of hepatitis C virus infection.

Small molecule screening, the systematic encounter of biology space with chemical space, has provoked the emergence of a whole industry that recreates itself by constant iterative improvements to this process. The authors describe an approach to tackle the problem for one of the most time-consuming steps in the execution of a screening campaign, namely, the reformatting of high-throughput screening test compounds from master plates to daughter assay plates used in the execution of the screen. Through an engineered storage procedure, they prepare plates ahead of the screening process with the respective compounds in a ready-to-use format. They show the biological inertness of the method and how it facilitates efficient recovery of compound activity. This uncoupling of normally interconnected processes provides time and compound savings, avoids repeated freeze-thaw cycles of compound solutions, and removes the problems associated with the DMSO sensitivity of certain assays types.

Translational pharmacokinetic–pharmacodynamic modelling; application to cardiovascular safety data for PF-00821385, a novel HIV agent

The synthesis and structure-activity relationships of a series of novel interferon inducers are described. Pharmacokinetic studies and efficacy assessment of a series of 8-oxo-3-deazapurine analogues led to the identification of compound 33, a potent and selective agonist of the TLR7 receptor with an excellent in vivo efficacy profile in a mouse model.