A decentralized solid compound storage facility managed by a centralized electronic platform at a growing drug discovery company

Within a growing drug discovery company, scientists acquire (either through in house synthesis or purchase) then store, retrieve, and ship solid compound samples daily between multiple locations. The efficient management and tracking of this entire process to support drug discovery is a significant challenge. This article describes a decentralized and cost-effective inventory facility that simplifies the solid compound storage and retrieval process. Standardized storage cabinets from the market are utilized, providing a cost-effective physical infrastructure. The cabinets can be distributed across storage rooms at multiple sites and arranged into spaces with a variety of dimensions, allowing the system to be retrofitted into existing facilities and scaled up easily. We can provide storage close to work areas at each location, minimizing both unnecessary movement of staff and transportation of substances. We have applied a systematic barcoding method to the compound batch identifier that correlates with its compound location. This simplifies the compound registration process as well as the process of finding and returning compounds. Additionally, a centralized electronic platform has been employed to store, update and track solid compound information, such as properties, location and quantity. Compound shipment may be initiated from different sites, and a centralized electronic platform assists the information retrieval process, ensuring each location possesses up-to-date information. The electronic platform we present streamlines the management of compound registration, location tracking, weight updates and shipment information, facilitating seamless record sharing among all stakeholders. Every step of the process can be tracked in real time by the project team. The platform can be flexibly configured to adapt to an evolving set of storage locations, with all information and processes being audited.

Advancing automation in Compound Management: a novel industrial process underpinning drug discovery

Faced with ageing infrastructure and ever-increasing demands from hit discovery and lead optimisation functions, AstraZeneca has chosen to develop innovative technologies and process solutions to support the future of drug discovery. These include the miniaturisation of compound storage tubes for high-density storage and rapid access to the corporate collection for feeding samples to the predicted tripling number of high throughput screening (HTS) campaigns. The acoustically- compatible tubes also enable the first fully-acoustic plate production process for faster sample supply to screening with less waste and continued high quality. Operating at a smaller scale reduces compound synthesis, storage, and consumption, prompting miniaturisation of upstream chemistry and downstream biological assays, while offering a transformative and sustainable solution to many drug discovery issues applicable across the industry.

Are there decision support tools that might strengthen the health system for perinatal care in South African district hospitals? A review of the literature

BACKGROUND

South Africa has a high burden of perinatal deaths in spite of the availability of evidence-based interventions. The majority of preventable perinatal deaths occur in district hospitals and are mainly related to the functioning of the health system. Particularly, leadership in district hospitals needs to be strengthened in order to decrease the burden of perinatal mortality. Decision-making is a key function of leaders, however leaders in district hospitals are not supported to make evidence-based decisions. The aim of this research was to identify health system decision support tools that can be applied at district hospital level to strengthen decision-making in the health system for perinatal care in South Africa.

METHODS

A structured approach, the systematic quantitative literature review method, was conducted to find published articles that reported on decision support tools to strengthen decision-making in a health system for perinatal, maternal, neonatal and child health. Articles published in English between 2003 and 2017 were sought through the following search engines: Google Scholar, EBSCOhost and Science Direct. Furthermore, the electronic databases searched were: Academic Search Complete, Health Source - Consumer Edition, Health Source - Nursing/Academic Edition and MEDLINE.

RESULTS

The search yielded 6366 articles of which 43 met the inclusion criteria for review. Four decision support tools identified in the articles that met the inclusion criteria were the Lives Saved Tool, Maternal and Neonatal Directed Assessment of Technology model, OneHealth Tool, and Discrete Event Simulation. The analysis reflected that none of the identified decision support tools could be adopted at district hospital level to strengthen decision-making in the health system for perinatal care in South Africa.

CONCLUSION

There is a need to either adapt an existing decision support tool or to develop a tool that will support decision-making at district hospital level towards strengthening the health system for perinatal care in South Africa.

Metrics and the effective computational scientist: process, quality and communication

Recent treatments of computational knowledge worker productivity have focused upon the value the discipline brings to drug discovery using positive anecdotes. While this big picture approach provides important validation of the contributions of these knowledge workers, the impact accounts do not provide the granular detail that can help individuals and teams perform better. I suggest balancing the impact-focus with quantitative measures that can inform the development of scientists. Measuring the quality of work, analyzing and improving processes, and the critical evaluation of communication can provide immediate performance feedback. The introduction of quantitative measures can complement the longer term reporting of impacts on drug discovery. These metric data can document effectiveness trends and can provide a stronger foundation for the impact dialogue.