Challenges in setting Permitted Daily Exposure (PDE) Limits for pharmaceuticals: A review

BACKGROUND: When more than one drug is manufactured at a shared facility or equipment in pharmaceutical manufacturing, the potential carry-over of the retained residue of existing drug product on product contact parts of the equipment to the next product can be a source of cross contamination. Permitted daily exposure (PDE) is derived based on the complete nonclinical and clinical data available and is a dose that is unlikely to cause adverse effects if an individual is exposed, by any route, at or below this dose every day over a lifetime. OBJECTIVE: The objective was to present a comprehensive review of available scientific knowledge for derivation of PDE. METHODS: PubMed and ScienceDirect databases were searched using keywords “PDE” and “pharmaceuticals” and all the relevant literature up to March 2021 was reviewed. We have also calculated PDEs for Tobramycin (CAS No. 32986-56-4) and Acetyl Salicylic Acid (ASA, CAS No. 50-78-2). RESULTS: This research will be useful for scientists working in the PDE domain. The given examples emphasize the importance of use of human data in calculating PDE. CONCLUSION: The duty of the risk assessor entrusted with setting PDEs is to derive a data driven, scientifically justified value that is safe for patients, while avoiding unjustified conservativeness that puts unnecessary burden on manufacturing.

Target competition for resources under multiple search-and-capture events with stochastic resetting

We develop a general framework for analysing the distribution of resources in a population of targets under multiple independent search-and-capture events. Each event involves a single particle executing a stochastic search that resets to a fixed location x r at a random sequence of times. Whenever the particle is captured by a target, it delivers a packet of resources and then returns to x r , where it is reloaded with cargo and a new round of search and capture begins. Using renewal theory, we determine the mean number of resources in each target as a function of the splitting probabilities and unconditional mean first passage times of the corresponding search process without resetting. We then use asymptotic PDE methods to determine the effects of resetting on the distribution of resources generated by diffusive search in a bounded two-dimensional domain with N small interior targets. We show that slow resetting increases the total number of resources M tot across all targets provided that ∑ j = 1 N G ( x r , x j ) < 0 , where G is the Neumann Green’s function and x j is the location of the j -th target. This implies that M tot can be optimized by varying r . We also show that the k -th target has a competitive advantage if ∑ j = 1 N G ( x r , x j ) > N G ( x r , x k ) .

KAJIAN LITERATUR: MODEL MENTAL DAN METODE EVALUASINYA

Mental models is an ability that must be possessed by students, so it is necessary to do a meaningful evaluation as a basis for developing students' mental models. However, in Indonesia research on the field of mental models is rarely done because of several factors, one of which is a lack of reference methods that can be used as an evaluation tool. The purpose of this article is to convey methods that can be used to evaluate mental models derived from published articles. The results of our study provide choices of methods that can be used, namely the AC-SMM, SSI, SMD and PDE methods