Eli Lilly (India)

ABSTRACTAimsWhile obesity is linked to increased cancer risk, evidence on the impact of intentional weight loss on obesity‐associated cancers (OACs) is limited. A systematic literature review (SLR) was conducted to assess the association between intentional weight loss and cancer incidence, including overall cancers and 13 OACs, from recent observational studies and clinical trials.MethodsStudies published between January 2019 and May 2023 were searched within MEDLINE, EMBASE, and CENTRAL. Studies assessing the relationship between intentional weight loss, defined as weight reduction via metabolic‐bariatric surgery (MBS) or lifestyle interventions, and cancer incidence were included. A dual independent review process was used to screen 1954 abstracts and 84 full‐text articles, and to extract data from 18 full studies. All discrepancies were resolved by another reviewer.ResultsOf the 18 studies included, 17 studies were observational, focusing on MBS as the method for achieving weight reduction. One randomised controlled trial examined the effect of intensive lifestyle intervention on weight reduction and found no significant association between intentional weight loss and cancer risk. Intentional weight loss was associated with decreased cancer incidence in 71.4% (n = 5/7) of studies for all cancers and 66.7% (n = 4/6) of studies for OACs, with reported risk reductions of 11% to 33% and 11% to 41%, respectively. For specific OACs, a greater number of studies indicated that weight reduction was associated with reduced occurrence of endometrial (4/4, 100%, 31%–53% risk reduction), female breast (5/9, 55.6%, 19%–50% risk reduction) and colorectal (4/7, 57.1%, 20%–60% risk reduction) cancers.ConclusionsThis SLR highlights the potential cancer risk‐reduction benefit of weight reduction for people with obesity.

Background Though biologics have changed the therapeutic landscape in moderate-to-severe plaque psoriasis (PsO), their high cost is a major cause for restricted usage. Objective To compare the relative efficacy (Psoriasis Area Severity Index (PASI) 90/100) and cost of biological agents available in India for moderate-to-severe PsO based on the cost per number needed to treat (NNT). Methods NNTs of biologicals derived from published network meta-analyses (NMA) for psoriasis area and severity index (PASI) 90&100, were used to calculate the cost per NNT by multiplying the NNT of a drug by the number of doses required and the corresponding market price in India. The calculated cost was based on the maximum retail price (MRP) at 12, 24, 52, and 104 weeks of treatment. Results The most economical drug based on MRP was ustekinumab (biosimilar). The cost per NNT (PASI100) was lowest for ixekizumab at all time points, followed by ustekinumab. For PASI90, the cost per NNT was lowest for ustekinumab at all time points, followed by ixekizumab. Limitations NNT values from previously published NMA data were used. Cost-per-NNT analyses were based on Randomised control trial (RCT) evidence and, thus, could not account for real-world factors that may impact the true cost of therapy. The cost of biologics varies due to the changes in the prices of the brands and the availability of biosimilars. Also, our analysis did not account for any adverse effects and their costs. Conclusion Ixekizumab and ustekinumab were the most cost-effective biologics to achieve PASI100 and PASI90, as cost per NNT analysis. This data can be used by procurement agencies and dermatologists to estimate the cost to patients on short and long-term bases.

Organic electrosynthesis opens new avenues of reactivity and promises more sustainable practices in the preparation of fine chemicals and pharmaceuticals. The full value of this approach will be realized by taking these processes to the production scale; however, achieving this goal will require a better understanding of the influence of mass transport on reaction behavior and the interactions between reactive species and electrodes inherent to organic electrosynthesis. The limited options for cell geometries used on small scale limit elucidation of these features. Here, we show how advanced cell geometries allow us to control the interplay between reaction mechanism and mass transport, leading to improved performance of three modern organic electrosynthetic reactions. Each reaction shows a unique relationship with mass transport, highlighting the importance of understanding this relationship further to maximize the utility of organic electrosynthesis at scale.

Computer-aided molecular design (CAMD) methods can be used to generate promising solvents with enhanced reaction kinetics, given a reliable model of solvent effects on reaction rates. Herein, we use a surrogate model parameterised from computer experiments, more specifically, quantum-mechanical (QM) data on rate constants. The choice of solvents in which these computer experiments are performed is critical, considering the cost and difficulty of these QM calculations. We investigate the use of model-based design of experiments (MBDoE) to identify an information-rich solvent set and integrate this within a QM-CAMD framework. We find it beneficial to consider a wide range of solvents in designing the solvent set, using group contribution techniques to predict missing solvent properties. We demonstrate, via three case studies, that the use of MBDoE yields surrogate models with good statistics and leads to the identification of solvents with enhanced predicted performance with few iterations and at low computational cost.

The combination ofethyl (hydroxyimino)cyanoacetate (Oxyma) anddiisopropylcarbodiimide (DIC) has demonstrated superior performancein amino acid activation for peptide synthesis. However, it was recentlyreported that Oxyma and DIC could react to generate undesired hydrogencyanide (HCN) at 20 °C, raising safety concerns for the practicaluse of this activation strategy. To help minimize the risks, thereis a need for a comprehensive investigation of the mechanism and kineticsof the generation of HCN. Here we show the results of the first systematiccomputational study of the underpinning mechanism, including comparisonswith experimental data. Two pathways for the decomposition of theOxyma/DIC adduct are derived to account for the generation of HCNand its accompanying cyclic product. These two mechanisms differ inthe electrophilic carbon atom attacked by the nucleophilic sp2-nitrogen in the cyclization step and in the cyclic productgenerated. On the basis of computed “observed” activationenergies, ΔGobs⧧, the mechanism that proceeds via theattack of the sp2-nitrogen at the oxime carbon is identifiedas the most kinetically favorable one, a conclusion that is supportedby closer agreement between predicted and experimental 13C NMR data. These results can provide a theoretical basis to developa design strategy for suppressing HCN generation when using Oxyma/DICfor amino acid activation.

Background: Ramucirumab plus docetaxel has been shown to improve survival as a second-line treatment for patients with Stage IV non-small-cell lung cancer (NSCLC) in the multicenter, double-blind, randomized, Phase III trial, REVEL. Objective: In this exploratory analysis, we aimed to assess the safety and efficacy of ramucirumab plus docetaxel in the Indian patient subgroup of the REVEL study. Materials and Methods: Adult patients with histologically or cytologically confirmed NSCLC of either squamous or non-squamous histology, who progressed during or after first-line platinum-based chemotherapy were randomized to receive either ramucirumab plus docetaxel or placebo plus docetaxel. We performed a descriptive analysis of the baseline characteristics, safety, and efficacy of the Indian subgroup of the overall REVEL study (NCT01168973). The analyses presented here are not intended for comparison purposes either between treatment arms or to the overall REVEL study. Results: Fifty-five Indian patients were included in the REVEL study. Baseline characteristics and prior therapies of these patients were well-balanced between the treatment arms. Almost 80% patients had non-squamous histology, and 78.2% were men. All patients had received prior standard platinum-based therapy: 25.5% of patients received maintenance, while 18.2% received taxane (paclitaxel only) as part of their first-line therapy. The incidence of treatment-emergent adverse events regardless of grade was similar between the two arms in the Indian safety subgroup. Patients treated with ramucirumab plus docetaxel experienced a median overall survival (OS) of 13.5 months (95% confidence interval [CI], 5.7–17.6) and progression-free survival (PFS) of 5.6 months (95% CI, 2.8–7.0) relative to a median OS of 5.3 months (95% CI: 3.6–9.9) and PFS of 1.5 months (95% CI: 1.3–5.2), for those treated with placebo plus docetaxel. Conclusion: In this exploratory analysis, Indian patients enrolled in the REVEL study demonstrated prolonged OS and PFS when treated with ramucirumab plus docetaxel, consistent with the overall results of the REVEL study. Ramucirumab plus docetaxel appears to be well tolerated by Indian patients, as the rates for most adverse events were similar with and without ramucirumab.

Diabetes is an increasing public health problem, and insulin is the mainstay for treatment of type 1 diabetes. In type 2 diabetes treatment, insulin therapy is used after oral or other injectable agents become inadequate to achieve glycemic control. Despite the advances in insulin therapy, management of diabetes remains challenging. Numerous studies have reported low adherence and persistence to insulin therapy, which acts as a barrier to successful glycemic control and diabetes management. The aim of this targeted review article is to provide an overview of adherence and persistence to insulin therapy in people with diabetes and to discuss the impact of the emergence of a new connected ecosystem of increasingly sophisticated insulin pens, glucose monitoring systems, telemedicine, and mHealth on diabetes management. With the emergence of a connected diabetes ecosystem, we have entered an era of advanced personalized insulin delivery, which will have the potential to enhance diabetes self-management and clinical management. Early systems promise to unlock the potential to address missed or late bolus insulin delivery, which should help to address non-adherence and non-persistence. Over time, improvements in this ecosystem have the potential to combine insulin data with previously missing contextualized patient data, including meal, glucose, and activity data to support personalized clinical decisions and ultimately revolutionize insulin therapy.