Cade oil poisoning: about a case.

Throughout Morocco, cade oil is used in folk medicine for many purposes, in particular for atopic dermatosis. It is also used as a wormer. Cade oil poisoning of newborns and infants thus often has an iatrogenic origin, resulting especially from the ingestion of a significant amount or from a prolonged and extensive cutaneous application. Thus, this oil, used for therapeutic purposes, is responsible for a non-negligible number of cases of poisoning, some fatal. We report a case of poisoning after cutaneous application of cade oil in a 2-month-old infant. The outcome was fatal. This report calls attention to the real possibility of this event and emphasizes the interest of preventing it by promoting information to families in Morocco.

Multiobjective long-term planning of biopharmaceutical manufacturing facilities.

Biopharmaceutical companies with large portfolios of clinical and commercial products typically need to allocate production across several multiproduct facilities, including third party contract manufacturers. This poses several capacity planning challenges which are further complicated by the need to satisfy different stakeholders often with conflicting objectives. This work addresses the question of how a biopharmaceutical manufacturer can make better long-term capacity planning decisions given multiple strategic criteria such as cost, risk, customer service level, and capacity utilization targets. A long-term planning model that allows for multiple facilities and accounts for multiple objectives via goal programming is developed. An industrial case study based on a large scale biopharmaceutical manufacturer is used to illustrate the functionality of the model. A single objective model is used to identify how best to use existing capacity so as to maximize profits for different demand scenarios. Mitigating risk due to unforeseen circumstances by including a dual facility constraint is shown to be a reasonable strategy at base case demand levels but unacceptable if demands are 150% higher than expected. The capacity analysis identifies where existing capacity fails to meet demands given the constraints. A multiobjective model is used to demonstrate how key performance measures change given different decision making policies where different weights are assigned to cost, customer service level, and utilization targets. The analysis demonstrates that a high profit can still be achieved while meeting key targets more closely. The sensitivity of the optimal solution to different limits on the targets is illustrated.