Needed: system dynamics for the drug discovery process

A simulation model to evaluate pharmaceutical supply chain costs in hospitals: the case of a Colombian hospital

BACKGROUND

Healthcare costs is one of the most studied issue in our days because of increasing demand and the aging of population. Final costs of medicines is one of the most important issue in patient treatment and determine its real value is an important task within hospitals. Simulation models and in this case system dynamics allows to build representations of reality considering the interaction of the whole variables that affect the system where first a causal loop diagram allows to represent and identify the interaction between variables for develop a stock flow diagram to determine the final results.

OBJECTIVE

Develop a simulation model that allows decision makers in Hospitals and Governments to identify the variables that affect the final cost of medicines and to determine the legal reimbursement allowed by national agencies.

METHODS

This paper presents a conceptual modeling framework using a causal loop diagram and a dynamic simulation model in the real case of a hospital in Colombia to explore how different internal charges for medicines affect the behavior of the final unit-dose cost of medicines, considering the complexity of the pharmaceutical system. We developed a simulation model to represent and characterize the pharmaceutical supply chain in a hospital and by using real data we validate the results of the model and conclude about the supply chain of medicines in Colombia using the legal regulations as a main factor of analysis.

RESULTS AND CONCLUSIONS

We found that in some cases the maximum reimbursement value is less than the final cost of medicines within the hospital, which means that hospitals lose money on the administration of medicines to patients. The benefit of this model is that with the result the hospital can determine the real final monetary value of medicines, including the different processes starting from the reception of the medicines, ending with the administration to patients.

A Primer on Screening Data Management

A drug discovery startup company or academic lab entering the screening arena faces numerous challenges as it tries to manage the large quantity of data generated by a typical drug discovery screening campaign. Although there are sophisticated off-the-shelf software solutions available, their use requires substantial forethought and attention to detail if the data they capture are to be of sufficient quality to serve the various purposes to which it will be put. For newcomers to the field of screening data management in particular, the problem is compounded by a lack of literature covering the practical aspects of managing screening data. The authors provide some practical advice based on their experience of using a commercially available software suite. They discuss issues ranging from the organizational aspects to examples of how the form and content of metadata can have a big impact on whether results can be easily queried, pivoted, and reported. It is also hoped that their experiences might provide an opportunity for reflection to data management practitioners operating in established environments.

Advances in improving the quality and flexibility of compound management

The process of drug discovery has evolved considerably since the advent of high-throughput screening (HTS) in the 1980s. Experts and opinion leaders today are agreeing that the current trend in the field is a focus on increasing overall quality (target, screening, and compounds), use of multiple screening approaches for lead discovery, and more flexibility in the process. The associated need for increased flexibility and quality control to support existing HTS paradigms as well as lower throughput approaches such as fragment screening, computational chemistry, focused library building, and centralized lead optimization support has required an evolution in compound management (CM, aka sample management or library management). Although there is much less published peer-reviewed data in CM, due to its historical links to HTS, it has followed very similar trends. In recent years, the focus in CM has been increasingly in compound quality and increased flexibility of the process, as opposed to number of compounds dispensed and speed of dispensing, which were standard metrics and indicators used not so long ago. Ideally, to screen the highest quality sample for every assay, one would start with a correct identity and pure solid, make a correct concentration solution in water or water-soluble/assay-compatible solvent that would allow 100% solubilization, and screen it immediately in a biological assay. Neither CM nor screening has advanced sufficiently to deliver this ideal scenario, but many significant advancements have been made in recent years both in terms of quality of compounds in stores and flexibility of the process, which will be reviewed herein.