Reconfiguring global pharmaceutical value networks through targeted technology interventions

Targeting a series of advanced manufacturing technology (AMT) ‘interventions’ provides the potential for significant step changes across the pharmaceutical value chain, from early stage ‘system discovery’ and clinical trials, through to novel service supply models. This research explores future value network configurations which, when aligned with disruptive shifts in technology (process and digital), may enable alternative routes to medicines production and the delivery of additional value to ‘end-users’, i.e. patients and health care providers. We draw on a categorisation of AMTs that may enable a shift from the traditional ‘batch’ and centralised manufacturing paradigm of ‘make-to-stock’, towards more re-distributed ‘continuous’ manufacturing and ‘make-to-order’ models. Despite reported benefits in the academic literature (e.g. reduced footprints, improved quality, enhanced flexibility and inventory savings), current adoption rates of continuous technologies in this sector remain low (c. 5%). This paper presents new data sources, in our study of AMT adoption in a global pharmaceutical context – assessing the barriers to implementation, and the pathways to delivering future continuous manufacturing scenarios. Our findings capture the high level of disparity in viewpoints, highlighting the uncertainties and transformational challenges ahead – in terms of opportunity areas, technological readiness and a future vision for the sector, as a whole

Connecting the Brain to Itself through an Emulation.

Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions

Supply Chain Management System in Indian Pharmaceutical Industries: Strategies and Best Practices

The Indian Pharmaceutical Industry incurs almost one third of its total cost from supply chain management systems. The SCM costs are relatively higher in India than other countries of the world amounting to 13 % of India’s GDP (Adhikari & Bora ,2014). For having an effective supply chain management system, it is required to have procurement of raw materials, raw materials turned into finished good and then further moved out in market for distribution. The major aspect in relation to SCM is the lack of knowledge on the various SCM related issues and strategies, most of the industries spend a lot of amount on the SCM issues and high resentment is on one specific problem i.e. of reduction in operational cost. However, the effectiveness also depends on SCM to be indispensable in maintaining expenses and seek ways to reduce cost thereby increasing the sales of the company. The purpose of the study is to explore various strategies and best practices involved which are used by the Indian business leaders of Pharma industries and finding out ways to maximize sourcing, distribution, inventory and its management. The methodology used is a single case study on various aspects with the semi- structured interview to collect data. The research design used on data sources identified were: observations, semi-structured Interview and documents of the industry. For the Identification of the challenges and their solutions in SCM strategies the proposed theory of Goldratt’s (1990), Theory of constraints was used as conceptual framework. The results of the study is a significant contribution to the business practices in the industries, increase in supply chain effectiveness, their strength and weakness, reducing organizational operational cost and socially finding the reputation of industries in ensuring the on time availability of their medicines in market. The study also relates, aims in identifying and implementing the best practices in various processes of Supply chain management by facilitating the increased availability, distribution of medicine, profitability and reduced operation cost

The Role of the Mangement Sciences in Research on Personalization

We present a review of research studies that deal with personalization. We synthesize current knowledge about these areas, and identify issues that we envision will be of interest to researchers working in the management sciences. We take an interdisciplinary approach that spans the areas of economics, marketing, information technology, and operations. We present an overarching framework for personalization that allows us to identify key players in the personalization process, as well as, the key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firm's value system. We review extant literature in the strategic behavior of firms, and discuss opportunities for analytical and empirical research in this regard. Next, we examine how a firm can learn a customer's preferences, which is one of the key components of the personalization process. We use a utility-based approach to formalize such preference functions, and to understand how these preference functions could be learnt based on a customer's interactions with a firm. We identify well-established techniques in management sciences that can be gainfully employed in future research on personalization.CRM, Persoanlization, Marketing, e-commerce,

ICT INDUSTRY INTEGRATED CURRICULA: TOWARDS AN ONTOLOGY BASED COMPETENCY MODEL

As technology advances rapidly, the ever changing industry needs for skills and competencies keeps changing in efforts to seize the nearest competitive advantage. This creates a great burden on higher education institutions to accurately be able to supply what the industry currently demands. Understanding and analyzing the gap between the supplied and demanded competencies has been always a topic of debate and research between both domains of knowledge. In this thesis, we have proposed developing an ontology that would help in identifying the gap between the employee and occupation competencies. The objective is to be able to generate the gap analysis utilizing the ontology and provide users with information that would help them in gaining more knowledge about the domain and taking informative decisions based on facts. Two separate ontologies representing classes and object properties of the Education and the Industry domain were successfully modeled. The validation shows that the ontology correctly classifies the employees as Fit or Un-fit to the set of occupations they applied for according to the competency gap analysis. Future work will involve experts validating the results of the ontology from the domain of knowledge point of view.QNRF project ProSkima NPRP 7-1883-5-28

Identifying bottlenecks in supply chains using visual analysis

Confidential until 24. May 202