The use of life cycle assessment as an early R&D decision tool: bottlenecks and potential solutions

At an ever increasing rate innovative chemistry and technology platforms are reshaping manufacturing environments to become factories of the future as being more productive, lean and flexible. The use of Life Cycle Assessment (LCA) in early process development phases has been challenged many times to assess whether or not this willingness to strive for innovation is an environmentally sustainable one. This paper provides general solutions to two major bottlenecks in applying LCA in R&D decision trees; (1) the lack of sufficient process data in early development phases and (2) the lack of knowledge on the effect of scale and learning on the environmental sustainability of a chemical product or process. The first issue is tackled with the use of multiple linear regression modeling, while for the second bottleneck the concept of deriving experience curves is proposed and illustrated. While this paper has taken a step in the direction of including LCA as a decision making tool in early process development phases, it stresses that more research should be conducted especially on Sustainable Supply Chain Management (SSCM), since it makes little sense to optimize in-house production without a proper procurement and Supply Chain Management (SCM)

Risk factors for femoral stem fracture following total hip arthroplasty : a systematic review and meta analysis

Background Femoral stem fracture following total hip arthroplasty (THA) is an infrequent but nevertheless devastating complication, with an increasing worldwide prevalence as demand for primary THA continues to increase. The aim of this study was to perform a systematic review and meta-analysis of risk factors for femoral stem fracture to help identify at risk patients. Methods A systematic search was conducted on EMBASE, MEDLINE and AMED to identify relevant studies. Data regard- ing study design, source, population, intervention, and outcomes was collated. Data extraction was performed on a custom form generated using Cochrane recommended methodology and analysis of risk factors performed including odds ratios (ORs) with 95% confidence intervals (CIs). Results A total of 15 studies reporting a total of 402 stem fractures in 49 723 THAs were identified. The median time from index procedure to stem fracture was 68 months (IQR 42.5–118) whilst mean age at index surgery was 61.8 years (SD 6.9). Male gender (OR = 3.27, 95% CI = 2.59–4.13, p < 0.001), patient weight above 80 kg (OR = 3.55, 95% CI = 2.88–4.37, p < 0.001), age under 63 years (OR = 1.22, 95% CI = 1.01–1.49, p < 0.001), varus stem alignment (OR = 5.77, 95% CI = 3.83– 8.7, p < 0.001), use of modular implants (OR = 1.95, 95% CI = 1.56–2.44, p < 0.01) and undergoing revision arthroplasty (OR = 3.33, 95% CI = 2.70–4.1, p < 0.001) were significant risk factors for prosthetic stem fracture. A risk window of 15 years post-surgery was identified. Conclusions This review concludes that patient weight, younger age, male sex, varus stem alignment, revision arthroplasty and use of modular stems are significant risk factors for femoral stem fracture. Modifying these risk factors where possible may help reduce incidence of femoral stem fracture in at risk patients.Peer reviewe

Streamlining life cycle assessments: an emerging need for simplification

At an ever increasing rate innovative chemistry and technology platforms are reshaping manufacturing environments to become factories of the future by being more productive, lean and flexible. The use of Life Cycle Assessment (LCA) in early process development phases has been challenged many a time to assess whether or not this willingness to strive for innovation is an environmentally sustainable one, often due to a lack of process data. This study takes the streamlining of LCA one step further and proposes an optimal complexity of modelled product systems in terms of their optimal set of predictor variables. Out of more than 2,800 Basic Operations (BOs) in pharmaceutical synthesis steps, candidate predictor variables were identified to forecast the environmental burden (in this case natural resource consumption) of a production step per unit of output. By means of backwards stepwise linear regression modelling, combinations of candidate predictors were tested and evaluated based on their predictive power (R²) and the model uncertainty. It was proven that at least the amount of organic solvents used, the molar efficiency and the time duration of the synthesis step should be included in the model (R² = 0.87) as being the most significant predictor variables. Including additional predictors however imposes no guarantee to contribute to the predictive power and eventually weakens the model interpretation and its simplicity. The results of the study were evaluated in the light of the product-specific versus product group approach debate. Should LCAs be generalized to such an extent that an extensively diversified product group is to be represented with an averaged burden, while fairly simplified and streamlined methods can represent product-specific impact assessments with a reasonable need for data, time and knowledge? The trade-off between simplicity and accuracy will be dealt with quantitatively in the oral presentation. Ideally, an organization should be able to derive its environmental impacts from readily available Enterprise Resource Planning (ERP) data, linking supply chains back to the cradle of resource extraction, excluding the need for an approximation with product group averages. While this study has taken a step in that direction, more research should be conducted especially on how efforts towards sustainable development should be addressed with care to valorise them efficiently in the supply chain and its sectors, beyond any company borders

Risk factors for femoral stem fracture following total hip arthroplasty:a systematic review and meta analysis

Background Femoral stem fracture following total hip arthroplasty (THA) is an infrequent but nevertheless devastating complication, with an increasing worldwide prevalence as demand for primary THA continues to increase. The aim of this study was to perform a systematic review and meta-analysis of risk factors for femoral stem fracture to help identify at risk patients. Methods A systematic search was conducted on EMBASE, MEDLINE and AMED to identify relevant studies. Data regard- ing study design, source, population, intervention, and outcomes was collated. Data extraction was performed on a custom form generated using Cochrane recommended methodology and analysis of risk factors performed including odds ratios (ORs) with 95% confidence intervals (CIs). Results A total of 15 studies reporting a total of 402 stem fractures in 49 723 THAs were identified. The median time from index procedure to stem fracture was 68 months (IQR 42.5–118) whilst mean age at index surgery was 61.8 years (SD 6.9). Male gender (OR = 3.27, 95% CI = 2.59–4.13, p &lt; 0.001), patient weight above 80 kg (OR = 3.55, 95% CI = 2.88–4.37, p &lt; 0.001), age under 63 years (OR = 1.22, 95% CI = 1.01–1.49, p &lt; 0.001), varus stem alignment (OR = 5.77, 95% CI = 3.83– 8.7, p &lt; 0.001), use of modular implants (OR = 1.95, 95% CI = 1.56–2.44, p &lt; 0.01) and undergoing revision arthroplasty (OR = 3.33, 95% CI = 2.70–4.1, p &lt; 0.001) were significant risk factors for prosthetic stem fracture. A risk window of 15 years post-surgery was identified. Conclusions This review concludes that patient weight, younger age, male sex, varus stem alignment, revision arthroplasty and use of modular stems are significant risk factors for femoral stem fracture. Modifying these risk factors where possible may help reduce incidence of femoral stem fracture in at risk patients

Risk factors for femoral stem fracture following total hip arthroplasty:a systematic review and meta analysis

Background Femoral stem fracture following total hip arthroplasty (THA) is an infrequent but nevertheless devastating complication, with an increasing worldwide prevalence as demand for primary THA continues to increase. The aim of this study was to perform a systematic review and meta-analysis of risk factors for femoral stem fracture to help identify at risk patients. Methods A systematic search was conducted on EMBASE, MEDLINE and AMED to identify relevant studies. Data regard- ing study design, source, population, intervention, and outcomes was collated. Data extraction was performed on a custom form generated using Cochrane recommended methodology and analysis of risk factors performed including odds ratios (ORs) with 95% confidence intervals (CIs). Results A total of 15 studies reporting a total of 402 stem fractures in 49 723 THAs were identified. The median time from index procedure to stem fracture was 68 months (IQR 42.5–118) whilst mean age at index surgery was 61.8 years (SD 6.9). Male gender (OR = 3.27, 95% CI = 2.59–4.13, p &lt; 0.001), patient weight above 80 kg (OR = 3.55, 95% CI = 2.88–4.37, p &lt; 0.001), age under 63 years (OR = 1.22, 95% CI = 1.01–1.49, p &lt; 0.001), varus stem alignment (OR = 5.77, 95% CI = 3.83– 8.7, p &lt; 0.001), use of modular implants (OR = 1.95, 95% CI = 1.56–2.44, p &lt; 0.01) and undergoing revision arthroplasty (OR = 3.33, 95% CI = 2.70–4.1, p &lt; 0.001) were significant risk factors for prosthetic stem fracture. A risk window of 15 years post-surgery was identified. Conclusions This review concludes that patient weight, younger age, male sex, varus stem alignment, revision arthroplasty and use of modular stems are significant risk factors for femoral stem fracture. Modifying these risk factors where possible may help reduce incidence of femoral stem fracture in at risk patients

Human Health Benefits and Burdens of a Pharmaceutical Treatment: Discussion of a Conceptual Integrated Approach

The effects of a pharmaceutical treatment have until now been evaluated by the field of Health Economics on the patient health benefits, expressed in Quality-Adjusted Life Years (QALYs) versus the monetary costs. However, there is also a Human Health burden associated with this process, resulting from emissions that originate from the pharmaceutical production processes, Use Phase and End of Life (EoL) disposal of the medicine. This Human Health burden is evaluated by the research field of Life Cycle Assessment (LCA) and expressed in Disability-Adjusted Life Years (DALYs), a metric similar to the QALY. The need for a new framework presents itself in which both the positive and negative health effects of a pharmaceutical treatment are integrated into a net Human Health effect. To do so, this article reviews the methodologies of both Health Economics and the area of protection Human Health of the LCA methodology and proposes a conceptual framework on which to base an integration of both health effects. Methodological issues such as the inclusion of future costs and benefits, discounting and age weighting are discussed. It is suggested to use the structure of an LCA as a backbone to cover all methodological challenges involved in the integration. The possibility of monetizing both Human Health benefits and burdens is explored. The suggested approach covers the main methodological aspects that should be considered in an integrated assessment of the health effects of a pharmaceutical treatment.JRC.H.8-Sustainability Assessmen

Environmental sustainability assessments of pharmaceuticals: an emerging need for simplification in life cycle assessments

The pharmaceutical and fine chemical industries are eager to strive toward innovative products and technologies. This study first derives hotspots in resource consumption of 2839 Basic Operations in 40 Active Pharmaceutical Ingredient synthesis steps through Exergetic Life Cycle Assessment (ELCA). Second, since companies are increasingly obliged to quantify the environmental sustainability of their products, two alternative ways of simplifying (E)LCA are discussed. The usage of averaged product group values (R2 = 3.40 × 10−30) is compared with multiple linear regression models (R2 = 8.66 × 10−01) in order to estimate resource consumption of synthesis steps. An optimal set of predictor variables is postulated to balance model complexity and embedded information with usability and capability of merging models with existing Enterprise Resource Planning (ERP) data systems. The amount of organic solvents used, molar efficiency, and duration of a synthesis step were shown to be the most significant predictor variables. Including additional predictor variables did not contribute to the predictive power and eventually weakens the model interpretation. Ideally, an organization should be able to derive its environmental impact from readily available ERP data, linking supply chains back to the cradle of resource extraction, excluding the need for an approximation with product group averages