Cancer is a devastating disease that takes the lives of hundreds of thousands of people every year. Due to disease heterogeneity, standard treatments, such as chemotherapy or radiation, are effective in only a subset of the patient population. Tumors can have different underlying genetic causes and may express different proteins in one patient versus another. This inherent variability of cancer lends itself to the growing field of precision and personalized medicine (PPM). There are many ongoing efforts to acquire PPM data in order to characterize molecular differences between tumors. Some PPM products are already available to link these differences to an effective drug. It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this. However, broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.

Personalized medicine strives to deliver the ‘right drug at the right dose’ by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based Pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver [(AAD)2] methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the Quality by Design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.

The rejection of process impurities from crystallizing products is an essential step for the purification of pharmaceutical drugs and for the isolation of active pharmaceutical ingredients with the right crystal quality attributes. While several impurity incorporation mechanisms have been reported in the literature, the frequency of those mechanisms in actual industrial processes is largely unknown. This work presents the outcome of a joint investigation by crystallization scientists from two pharmaceutical companies and an academic institution, on the prevalence of impurity retention mechanisms in cooling and antisolvent crystallizations. A total of 52 product-impurity pairs have been explored in detail using the so-called Solubility-Limited Impurity Purge (SLIP) test as the diagnostic tool to identify the underlying impurity retention mechanism of already crystallized materials with challenging impurities. The results show that formation of solid solutions is the most common mechanism, where the impurity and product are partially miscible in the solid state. In 73% of cases, only one solid solution phase was obtained in which the impurity became incorporated into the crystal lattice of the product (α phase). In 6% of the examples, two solid solution phases were obtained, where the second solid phase (β phase) comprised predominantly the impurity and the product was the minor component. The remaining impurity retention mechanisms (21%) are related to solid-state immiscible impurities that precipitated from solution resulting in a physical mixture between the product and the impurity. The reasons for the results are discussed through a comprehensive analysis of theoretical reported retention mechanisms, which includes physical constraints for the scale-up of isolation processes, thermodynamic assessments using ternary phase diagrams, and restrictions in the context of current pharmaceutical syntheses of small organic molecules. Three industrial case studies are presented that exemplify how knowledge of the retention mechanisms can be used to delineate appropriate strategies for process design and to effectively purge these impurities during crystallization or washing.

Synchronization of biological functions to environmental signals enables organisms to anticipate and appropriately respond to daily external fluctuations and is critical to the maintenance of homeostasis. Misalignment of circadian rhythms with environmental cues is associated with adverse health outcomes. Cortisol, the downstream effector of hypothalamic-pituitary-adrenal (HPA) activity, facilitates synchronization of peripheral biological processes to the environment. Cortisol levels exhibit substantial seasonal rhythmicity, with peak levels occurring during the short-photoperiod winter months and reduced levels occurring in the long-photoperiod summer season. Seasonal changes in cortisol secretion could therefore alter its entraining capabilities, resulting in a season-dependent modification in the alignment of biological activities with the environment. We develop a mathematical model to investigate the influence of photoperiod-induced seasonal differences in the circadian rhythmicity of the HPA axis on the synchronization of the peripheral circadian clock and cell cycle in a heterogeneous cell population. Model simulations predict that the high-amplitude cortisol rhythms in winter result in the greatest entrainment of peripheral oscillators. Furthermore, simulations predict a circadian gating of the cell cycle with respect to the expression of peripheral clock genes. Seasonal differences in cortisol rhythmicity are also predicted to influence mitotic synchrony, with a high-amplitude winter rhythm resulting in the greatest synchrony and a shift in timing of the cell cycle phases, relative to summer. Our results highlight the primary interactions among the HPA axis, the peripheral circadian clock, and the cell cycle and thereby provide an improved understanding of the implications of circadian misalignment on the synchronization of peripheral regulatory processes.

Agitated drying of pharmaceuticals remains a challenging manufacturing step due to the simultaneous heat transfer, mass transfer, and physicochemical changes occurring during the process. This work focuses on the heat transfer component by implementing the discrete element method to model dry particles in a heated bladed mixer. Simulations varying material conductivities and impeller agitation rates were conducted to evaluate the influence on the mean bed temperature and distribution. The results indicated that increasing the agitation rate generally improved heat transfer up until a critical agitation rate where the rate of heat transfer plateaued. The magnitude of this improvement in heat transfer depended on the material's thermal properties. We observed three regimes: a conduction‐dominated regime where particles heated quickly but with an annular temperature gradient, a granular convection‐dominated regime where particles heated slowly but uniformly, and an intermediate regime. The results were nondimensionalized to enable predictions and help inform drying protocols.

An understanding of heat transfer in a bladed mixer is important for drying of pharmaceutical drug crystals. This study presents thermal imaging experiments of the particle bed surface in a bladed mixer to investigate how the impeller speed influences the rate and the uniformity of heat transfer. Next, the process is simulated using the discrete element method. The bed thermal properties are lumped into an effective thermal conductivity, that is calibrated for one impeller speed. The experiments and the simulations show the same trends and generally agree well for all agitated beds. However, to obtain good agreement of the rate of heat transfer between the simulations and experiments in a static bed, we need to adopt a higher thermal conductivity than for the agitated beds. Finally, we discuss the implications of these results for the design of operating protocols.

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

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