Robust Model Selection: Flatness-Based Optimal Experimental Design for a Biocatalytic Reaction

Considering the competitive and strongly regulated pharmaceutical industry, mathematical modeling and process systems engineering might be useful tools for implementing quality by design (QbD) and quality by control (QbC) strategies for low-cost but high-quality drugs. However, a crucial task in modeling (bio)pharmaceutical manufacturing processes is the reliable identification of model candidates from a set of various model hypotheses. To identify the best experimental design suitable for a reliable model selection and system identification is challenging for nonlinear (bio)pharmaceutical process models in general. This paper is the first to exploit differential flatness for model selection problems under uncertainty, and thus translates the model selection problem to advanced concepts of systems theory and controllability aspects, respectively. Here, the optimal controls for improved model selection trajectories are expressed analytically with low computational costs. We further demonstrate the impact of parameter uncertainties on the differential flatness-based method and provide an effective robustification strategy with the point estimate method for uncertainty quantification. In a simulation study, we consider a biocatalytic reaction step simulating the carboligation of aldehydes, where we successfully derive optimal controls for improved model selection trajectories under uncertainty

A Perspective on the Role of Digitalization Enablers in Sustainable Pharmaceutical Manufacturing

Due to the steady rise in the implementation of Industry 4.0 concepts in chemical and (bio)pharmaceutical industries, an essential aspect of transitioning pharmaceutical production towards Sustainable Pharmaceutical Manufacturing (SPM) is the utilization of digitalization technologies. SPM involves the collaboration of a multitude of different process engineering and sustainability-oriented systems methodologies like Lifecycle Assessment and green metrics. Keeping this in mind, this paper aims to provide a concise review of critical areas of digitalization aspects to overcoming the hurdles towards sustainability of pharmaceutical processes: process analytical technologies (PATs), soft sensors and Digital Twins (DTs). These tools enable manufacturing under the Quality-by-Design (QbD) paradigm, prioritizing process and product understanding and yield to reduce the number of tests, resources, and costs in the long run. Modernization through DTs and PAT requires significant data exchange and a fully realized data management system. Successful integration of digitalization, I4.0, and lean manufacturing concepts have been found to be of substantial advantage for flexible supply chains and continuous manufacturing, higher efficiencies, and productivity with minimal waste production. The path to utilizing these tools to their full potential in the pharmaceutical industry is closely examined for application in specific processes and products in the future

The other GMP: good manufacturing practice and its importance in the validation of constructed pharmaceutical facilities

The work reported is part of an ongoing PhD study prompted by the particular difficulties encountered when two very different quality cultures interact (in this case Pharmaceutical industry clients and Construction industry providers). Pharmaceutical facilities have particular needs for their production requirements. Stringent regulations are set by regulatory bodies such as the Medicines and Healthcare products Regulatory Agency (MHRA) (in the UK) and the Food and Drugs Administration (FDA) in the US. This creates special problems of quality when it comes to the commissioning, validation and hand-over of the building, as it appears to be at odds with the rather less demanding quality systems that are normally accepted in the construction sector. The aim of the research is to model an acceptable process for incorporating these stringent validation requirements into the design, procurement and construction processes. There is little or no specific academic literature on the subject, though the trades and professional press (particularly in the USA) provide some normative comment on the problem area. The main academic grounding of the research is in Systems Theory and empirical data is being collecting using a multiple case study approach. Research data was collected from a number of pharmaceutical facility construction case studies and was used to test and inform a best practice model of facility validation. The qualitative methods of participant and direct observation were used as the main information gathering tools. The paper reports on the regulatory expectations that influence the construction of projects of this type and the impact on the best practice model of validation

New Product Development and Supply Chains in the Pharmaceutical Industry

The concept of chemical supply chain has received increased attention in the process systems engineering community in the last decade. This chapter discusses the methods, tools, and applications, which are relevant to the pharmaceutical industry. Among the various supply chains that have been studied, pharmaceutical supply chains turn out to be very complex, due to several factors such as long development timelines, high attrition rates in drug development, resource-intensive operations, involvement of multiple stakeholders, among others. A fundamental challenge in managing a pharmaceutical company is identifying the optimal allocation of finite resources across the infinite constellation of available investment opportunities. Specific attention is given here to the modeling and optimization of three key phases in the life cycle of an innovative drug product, namely, product development pipeline management, capacity planning, and supply chain management. The state of the art in these domains is reviewed, some challenges are identified, and opportunities for further research effort are highlighted

3D Printed Soft Robotic Hand

Soft robotics is an emerging industry, largely dominated by companies which hand mold their actuators. Our team set out to design an entirely 3D printed soft robotic hand, powered by a pneumatic control system which will prove both the capabilities of soft robots and those of 3D printing. Through research, computer aided design, finite element analysis, and experimental testing, a functioning actuator was created capable of a deflection of 2.17” at a maximum pressure input of 15 psi. The single actuator was expanded into a 4 finger gripper and the design was printed and assembled. The created prototype was ultimately able to lift both a 100-gram apple and a 4-gram pill, proving its functionality in two prominent industries: pharmaceutical and food packing

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Ready for Tomorrow: Demand-Side Emerging Skills for the 21st Century

As part of the Ready for the Job demand-side skill assessment, the Heldrich Center explored emerging work skills that will affect New Jersey's workforce in the next three to five years. The Heldrich Center identified five specific areas likely to generate new skill demands: biotechnology, security, e-learning, e-commerce, and food/agribusiness. This report explores the study's findings and offers recommendations for improving education and training in New Jersey

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Real-time assessment of critical quality attributes of a continuous granulation process

There exists the intention to shift pharmaceutical manufacturing of solid dosage forms from traditional batch production towards continuous production. The currently applied conventional quality control systems, based on sampling and time-consuming off-line analyses in analytical laboratories, would annul the advantages of continuous processing. It is clear that real-time quality assessment and control is indispensable for continuous production. This manuscript evaluates strengths and weaknesses of several complementary Process Analytical Technology (PAT) tools implemented in a continuous wet granulation process, which is part of a fully continuous from powder-to-tablet production line. The use of Raman and NIR-spectroscopy and a particle size distribution analyzer is evaluated for the real-time monitoring of critical parameters during the continuous wet agglomeration of an anhydrous theophylline− lactose blend. The solid state characteristics and particle size of the granules were analyzed in real-time and the critical process parameters influencing these granule characteristics were identified. The temperature of the granulator barrel, the amount of granulation liquid added and, to a lesser extent, the powder feed rate were the parameters influencing the solid state of the active pharmaceutical ingredient (API). A higher barrel temperature and a higher powder feed rate, resulted in larger granules

Emergence of the Biosimilar Sector and Opportunities of Developing Country Suppliers

As biologic products begin to come off-patent, a market is emerging for biosimilars (also known as biogenerics or follow-on biologics). Firms from emerging countries such as India and China have dominated the production of active ingredients in pharmaceutical industries all over the world and are now developing capabilities in biosimilar production. This emergence of a new market dynamic is disruptive to current key players as it has potential challenge their current dominant hold over the market, while for firms from developing countries it creates a sea of opportunities. This rise of biosimilars and capabilities for cheap production in developing country firms has potential to transform patient care in developing countries as well as advanced countries. This paper reviews study data collected at Innogen and the most recent literature to understand how the sector for biosimilars is evolving and the opportunities and challenges faced by emerging suppliers. The aim of the paper is to identify the gaps in the current literature and opportunities for further study in this area