Pharmaceutical management through environmental product labeling in Sweden.

There is an increased awareness that medicinal products for human use may cause negative effects in the environment. In Sweden a voluntary environmental classification system for drugs has been established in collaboration between producers, authorities and the public health care, and used for five years. The idea is to enhance the market demand for medicines with less environmental impact, which in turn will stimulate the producers to design future medicines to be more environmentally friendly. The system is open to the public and based on assessment of the active ingredient in the medicinal product into several classes of risk and hazard, respectively. It is closely related to the EMEA guidelines. Risk is expressed as the ratio between the predicted environmental concentration (PEC) of the active ingredient (AI) and its predicted no effect concentration (PNEC). The hazard is expressed in terms of the AI's persistence, potential to bioaccumulation, and eco-toxicity. Drug data for the classification are delivered by the respective producers. Hitherto more than 300 AI, representing more than 50% of the Swedish volume of drug use, have been classified. Data for risk assessment were missing in 47% of AI. Among drugs with data 7% had a PEC/PNEC ratio >1, and another 7% had a ratio between 0.1 and 1. The AIs with highest ratio (>10) were two estrogens. Data for hazard assessment were lacking in 16% of the AI. Among drugs with environmental data 92% were not ready biodegradable, 23% had potential to bioaccumulation, and 61% were toxic to aquatic organisms at a concentration below 1 mg/l. These data are utilized by regional pharmaceutical expert groups when selecting substances to be recommended in public health care in Sweden. They may also be used by prescribing doctors who want to identify the environmentally most favourable substance among several with equivalent medical effect. We conclude that environmental data on human medicinal products are often missing, or reveal unfavourable environmental properties. A proper judgement of the environmental impact of an AI requires a joint evaluation of its risk and hazard. We suggest that the pharmaceutical producers should highlight environmental precaution when designing new AIs, and that the environmental data should be transparent to the general public.