India Private Research Articles

A review on privatization in India

The growth of private businesses free of functionary management is a noteworthy feature of India's economic reforms. The public sector in this country requires modernization since it contributes significantly to national investment and development. As a result, the purpose of this essay is to examine the partial privatization and restructuring of India's state-owned companies (SOEs), which need more dynamic shape. Since India switched to market-based pricing and incentives with improved contract enforcement, central government SOEs have increased their profitability, investments, and growth. SOEs outperform private businesses in terms of profitability and efficiency in the industrial sector. SOEs, on the other hand, do worse in the service sector than their competitors. Finally, the research makes policy recommendations for improving SOE performance in India. In many countries, including India, improving the efficiency and performance of public sector banks (PSBs) is a major goal of economic reforms. Private ownership is thought to assist enhance efficiency and performance. As a result, the Indian government began gradually reducing its ownership in PSBs in the early 1990s. Is it true that partially privatizing Indian banks has improved their efficiency and performance? The data on the effect of privatization across the world is varied. Despite the fact that the problem is significant in India, no research has addressed it to the author's knowledge. As a result, the current research fills a significant gap.

High Efficacy of a Low Dose Candidate Malaria Vaccine, R21 in 1 Adjuvant Matrix-M™, with Seasonal Administration to Children in Burkina Faso

Background: Stalled progress in controlling Plasmodium falciparum malaria highlights the need for an effective and deployable vaccine. RTS,S/AS01, the most effective malaria vaccine candidate to date, demonstrated 55·8% (97·5% confidence interval [CI], 51-60) efficacy over 12 months in African children. Methods: We conducted a double-blind, randomised, controlled trial of a low-dose circumsporozoite protein-based vaccine, R21, with two different doses of adjuvant, Matrix-M™ (MM), in children aged 5-17 months in Nanoro, Burkina Faso, a highly seasonal malaria transmission setting. Three vaccinations were administered at 4-week intervals prior to the malaria season with a fourth dose one year later. Vaccine safety, immunogenicity and efficacy were evaluated over one year. Findings: 450 children were randomised to receive the R21/MM vaccine or a control rabies vaccine. R21/MM had a 43 favourable safety profile and was well-tolerated. At 6 months, 43/146 (29·5%) who received R21/MM with low44 dose adjuvant, 38/146 (26%) who received R21/MM with high-dose adjuvant, and 105/147 (71·4%) who received the rabies vaccine developed clinical malaria. Vaccine efficacy (VE) was 74% (95% CI, 63-82) and 77% (95% CI, 67-84) in the low- and high-dose adjuvant groups, respectively. At 1 year, VE remained high at 77% (95% CI, 67-84) in the high-dose adjuvant group. Participants vaccinated with R21/MM showed high titres of malaria-specific anti-NANP antibodies 28 days after the third vaccination, which were almost doubled with the higher adjuvant dose. Titres waned but were boosted to levels similar to peak titres following the primary series of vaccinations after a fourth dose administered one year later. Interpretation: R21/Matrix-M appears safe and very immunogenic in African children, and demonstrates promising high-level efficacy. Trial Registration: ClinicalTrials.gov number: NCT03896724. Funding: The European & Developing Countries Clinical Trials Partnership (EDCTP), The Wellcome Trust and the NIHR Oxford Biomedical Research Centre. Declaration of Interest: AVSH and KJE are named as co-inventors on patent applications related to R21. GG, LF, JR and PP-A are employees of Novavax, developers of the Matrix-M adjuvant, and US is an employee of the Serum Institute of India Private Ltd, co-developer of the R21/MM vaccine. Other authors declare no competing interests. Ethical Approval: The trial was approved by the Comite d’Ethique pour la Recherche en Sante, Burkina Faso (CERS, reference number 2019-01-012), and by the national regulatory authority, Agence National de Regulation Pharmaceutique, Burkina Faso (ANRP, reference number 5005420193E). Ethical approval was also granted in the United Kingdom by the Oxford Tropical Research Ethics Committee (OxTREC reference number 19-19).

Prices of combination medicines and single-molecule antihypertensive medicines in India's private health care sector.

More than half of patients with hypertension require two or more medicines to control blood pressure. Combinations of anti‐hypertensive medicines are available as Single Pill Combinations (SPCs) or Single Agent Pills (SAPs). SPCs of two or more anti‐hypertensive medicines facilitate simpler dosing schedules, decrease pill burden, increase adherence to medicine, and simplify procurement and distribution. Despite this, equivalent combinations of separate pills (SAPs) are often prescribed instead of SPCs under the assumption that SAPs are priced lower. This study compared prices of anti‐hypertensive SPCs and equivalent SAPs in the private health care sector of India. High sales volume anti‐hypertensive SPCs and SAPs were selected from 2018 private sector pharmaceutical sales data. SPCs and SAPs price information was collected from online pharmacy websites between November 2019 and January 2020. Anti‐hypertensive SPCs represent approximately 39.1% of India's private sector anti‐hypertensive drug market. Multiple manufacturers produce the same top‐selling SPCs, suggesting a viable and competitive market. A comparison of SPCs and SAPs across different manufacturers showed that the lowest prices of both SPCs and the sum of component SAPs were nearly identical across different manufacturers. An analysis of dual‐drug SPCs and SAPs by the same manufacturer showed that most manufacturers (five of six) had priced their SPCs higher than SAPs. These observations suggest that the price of SPCs could be lowered to match the combined price of the component SAPs, and manufacturing costs and market forces do not present a barrier to the implementation of anti‐hypertensive SPCs.

Superior Therapy Response Predictions for Patients with Myelodysplastic Syndrome (MDS) Using Cellworks Singula™: Mycare-020-02

Background: Therapy selection for MDS patients is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of MDS patients remains relatively poor. The Cellworks Singula™ report predicts response for physician prescribed treatments using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. Methods: The performance of Singula™ was evaluated in an independent, randomly selected, retrospective cohort of 144 MDS patients aged 28 to 89 years (median 69). The pre-defined Singula™ Classifier utilizes an individual's genomics profile to provide a dichotomous prediction of response or non-responses to a given physician prescribed treatment (PPT). Outcome data for these subjects, including measurement of complete response (CR), were obtained from 42 PubMed publications, each including patient genomics data of either karyotyping, targeted gene panels, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized these data to generate a Singula™ classifier of responder vs non-responder in this MDS cohort. Statistical analyses, including assessments of accuracy, sensitivity, specificity, negative (NPV) and positive predictive (PPV) values were performed on the merged data to compare the Singula™ predicted response with the actual observed CR. Multivariate logistic regression models of complete response were performed incorporating covariates for patient age, PPT, and the Singula™ Classifier. Results: Table 1 reveals that the pre-defined Singula™ classifier had 90.3% (Exact 95% CI: 84.2%, 94.6%) accuracy in predicting observed patient response from the physician prescribed treatment. In this study, Singula™ was able to accurately identify responders with 90.0% (81.2%, 95.6%) sensitivity. Importantly, Singula™ had 90.6% (80.7%, 96.5%) specificity for the subset of 64 patients (44.4%) that had a non-response. For 32% (17/54) of the non-responders patients, Singula™ provided an alternative Standard of Care treatment therapy, as shown in Table 2. The remaining 37 patients were predicted to be non-responders to all remaining Standard of Care options, so did not have alternate treatment predictions. Assuming at least 4% of these non-responding patients would have responded to the alternative Singula™ prescribed therapy, then these data support that Singula™ improves prediction of CR compared to the original PPT (McNemar's p-value < 0.05). In multivariate logistic regression models of CR that included patient age and prescribed drug therapy, the Singula™ Classifier remained an independent, significant predictor of CR (OR > 100, p-value < 0.0001), while both patient age (p = 0.372) and drug therapy (p = 0.720) fell off the model. Conclusions: Cellworks Singula™ has high accuracy and sensitivity in predicting CR for MDS patient response to physician prescribed therapies. Singula™ also has high specificity in identifying patients who are unlikely to respond to physician prescribed therapies and provides alternative treatment recommendations for these patients. The Singula™ Classifier is an independent and superior predictor of CR compared with other clinical (age) or therapeutic (PPT) factors. Figure Disclosures Stein: Amgen: Consultancy, Speakers Bureau; Stemline: Consultancy, Speakers Bureau. Watson:BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Prakash:Cellworks Research India Private Limited: Current Employment. Behura:Cellworks Research India Private Limited: Current Employment. Balakrishnan:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Marcucci:Abbvie: Speakers Bureau; Novartis: Speakers Bureau; Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial); Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Iaso Bio: Membership on an entity's Board of Directors or advisory committees.

Prediction of Clinical Response for Frontline Treatment of Acute Myeloid Leukemia (AML) Patients Using the Cellworks Omics Biology Model (CBM): Mycare-021-02

Background: AML is a heterogeneous hematological cancer, characterized by the clonal expansion of myeloid blasts in the peripheral blood, bone marrow and other tissues. Among adults, AML is the leading cause of leukemia-associated death. Patients are often elderly and have comorbid conditions. Response to remission induction therapy varies by biologic subtype and by the drugs used for induction, but responses to each therapy are not predictable, even within specific biologic subgroups. To improve prognostication and identify new therapeutic options, Cellworks developed the Cellworks Omics Biology Model (CBM) that relies on multi-omics inputs from malignant cells to predict response and identify potential therapies tailored to the unique mechanisms of each patient's disease. Aim: To predict the response to induction chemotherapy regimens in AML patients and identify predictive genomic signatures, pathways, and personalized treatment options for refractory patients. Method: 57 AML patients with known therapy response were selected from 8 PubMed publications (Table 1). The cohort was split into 3 groups with CBFB-MYH11 fusion (n=19), RUNX1-RUNX1T1 fusion (n=10) and CEBPα del (n=28). All data was anonymized, de-identified and exempt from IRB review. NCCN offers specific recommendations for AML patients with these mutations and they are associated with high rates of remission after induction therapy. The available genomic data for each profile was processed using Cellworks' CBM to generate an AML subtype-specific protein network map using published information from PubMed and other online resources permitting patient-specific biomarkers to be mapped to sensitivity and resistance pathways. Drugs selected from a digital drug library were simulated for each patient across the three cohorts. Benefit was assessed by measuring each drug's effect on a cell growth score, a composite of proliferation, viability, and apoptosis indices. Results: Of 57 patients with favorable-risk AML, 6 (11%) experienced induction failure. 1/19 patients harboring CBFB-MYH11 fusion failed to respond to induction therapy (Table 2) and CBM identified co-occurring gene aberrations responsible for resistance in the patient with resistant disease (ID:757637), who harbored trisomy 6 with amplification of GSTA1, GSTA2, GSTA4, DEK, TFAP2A, NFYA and EHMT2 causing dysregulation of pathways involved in treatment failure. CBM also identified 3 prospective therapies that target this patient's specific biomarkers (Table 3). Similarly, 2/10 patients with RUNX1-RUNX1T1 fusion failed to respond to induction therapy. CBM identified a loss of function mutation in EZH2 causing increased levels of HOXA5 and HOXA9 as key orchestrators of treatment failure (Patient ID: 757805). Furthermore, CBM also identified 3 prospective therapies for this patient, targeting patient-specific resistance mechanisms (Table 3). In the CEBPα cohort, 3/28 patients did not respond to induction therapy (Table 2). For Patient ID:755125, CBM identified a DNMT3A loss of function mutation and consequential gain in the levels of HOXA5 and HOXA9 as key orchestrators of treatment failure. Again, CBM identified 3 novel therapies for this patient targeting patient-specific biomarkers (Table 3). Conclusion: Even in biological subgroups of AML expected to have sensitive disease, induction failure is not rare. Fortunately, the CBM could identify causes of failure and suggest alternative therapies based on co-occurring genomic abnormalities to mitigate the ineffectiveness of standard induction regimens in patients with resistant disease despite their favorable biology. The identification of patient-specific resistance mechanisms characterizes a new therapeutic imperative founded on deep molecular diagnosis that promises to enhance disease outcomes, inform treatment planning, avoid adverse events from ineffective therapies, and reduce costs. Also, computational modeling identifies alternate therapy regimens for refractory patients by incorporating patient-specific disease biomarkers. For all the non-responders, CBM identified 3 potential therapies across each fusion subgroup. Although these combinations need further validation in the clinic, the Cellworks CBM biosimulation platform allows for precision medicine approaches that target patient-specific disease biomarkers and treatment resistance mechanisms. Disclosures Castro: Cellworks Group Inc: Consultancy. Nair:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Kumar:Cellworks Research India Private Limited: Current Employment. Agarwal:Cellworks Research India Private Limited: Current Employment. Suseela:Cellworks Research India Private Limited: Current Employment. Gopi:Cellworks Research India Private Limited: Current Employment. Ganesh:Cellworks Research India Private Limited: Current Employment. Shyamasundar:Cellworks Research India Private Limited: Current Employment. Kulkarni:Cellworks Research India Private Limited: Current Employment. Sauban:Cellworks Research India Private Limited: Current Employment. Balla:Cellworks Research India Private Limited: Current Employment. Chafekar:Cellworks Research India Private Limited: Current Employment. Choudhury:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Howard:Boston Scientific: Consultancy; Cellworks: Consultancy; EUSA Pharma: Consultancy; Sanofi: Consultancy, Other: Speaker; Servier: Consultancy, Other: Speaker.

Predicting Resistance to the Combination of ATO and ATRA in APL Patients with PML-Rara Fusions, Using a Computational Biology Modeling Approach: Mycare-021-01

Background: Acute promyelocytic leukemia (APL) is a biologically and clinically distinct subtype of acute myeloid leukemia (AML) with unique molecular pathogenesis, clinical manifestations, and treatment. APL is cytogenetically characterized by a balanced translocation t(15;17) (q24;q21), which involves the retinoic acid receptor alpha (RARA) gene on chromosome 17 and the promyelocytic leukemia (PML) gene on chromosome 15 that results in a PML-RARA fusion gene (PMID: 30575821). The PML-RARA fusion gene is the most critical event involved in the pathogenesis of APL, reported in 99% of APL patients (PMID: 32182684). The fusion confers a selective sensitivity to the targeted drugs, arsenic trioxide (ATO) and all-trans-retinoic acid (ATRA), with response rates over 90% (PMID: 31635329). However, the mechanism of resistance in the minority of non-responders is not well understood. This study used the Cellworks Omics Biology Model (CBM) to predict response to the combination of ATO-ATRA in patients harboring the PML-RARA fusion and identify mechanisms of resistance. Methods: Outcomes of 30 APL patients treated with ATRA or ATRA plus ATO were compared with outcomes predicted by CBM (Table 1). Genomic data from 6 publications (Table 2) derived from whole exome sequencing (WES), targeted next-generation sequencing (NGS), copy number variation (CNV) and/or karyotype data were used. All data was anonymized, de-identified and exempt from IRB review. The available genomic data for each profile was entered into the CBM which generates a patient-specific disease protein network model using PubMed and other online resources. The CBM predicts the patient-specific biomarker and phenotype response of a personalized diseased cell to drug agents, radiation and cell signaling. Disease biomarkers that are unique to each patient were identified within the protein network models. ATO and ATRA were simulated on all 30 patient cases. The treatment impact was assessed by quantitatively measuring the drug's effect on a cell growth score which is a composite of the quantified values for cell proliferation, survival, and apoptosis, along with the simulated impact on each patient-specific disease biomarker score. Each patient-specific model was also digitally screened to identify response to ATO and ATRA. Results: The CBM correctly predicted the response to ATO and ATRA in 28 of 30 cases. The overall prediction accuracy was 93% with a PPV of 100%, NPV of 60%, sensitivity of 93%, and specificity of 100%. In 2 of 30 patients who did not respond to ATO and ATRA, the CBM identified clinically relevant deletions to EZH2, KMT2E, and HIPK2 genes. All three genes are located on chromosome 7 and these non-responders had monosomy 7. Conclusions: The Cellworks Omics Biology Model predicted response to ATO and ATRA in APL patients harboring PML-RARA fusions. Predicting non-response to ATO and ATRA in patients with PML-RARA fusion up-front could prevent ineffective treatment, avoid unnecessary adverse events and reduce treatment costs. Additionally, computational modeling can identify new mechanisms of resistance and suggest alternative regimens for non-responding patients by targeting the patient-specific disease biomarkers unique to each. Disclosures Howard: Servier: Consultancy, Other: Speaker; Boston Scientific: Consultancy; Sanofi: Consultancy, Other: Speaker; EUSA Pharma: Consultancy; Cellworks: Consultancy. Nair:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Tyagi:Cellworks Research India Private Limited: Current Employment. Kumari:Cellworks Research India Private Limited: Current Employment. Prasad:Cellworks Research India Private Limited: Current Employment. Mitra:Cellworks Research India Private Limited: Current Employment. Lala:Cellworks Research India Private Limited: Current Employment. Azam:Cellworks Research India Private Limited: Current Employment. Gupta:Cellworks Research India Private Limited: Current Employment. Mohapatra:Cellworks Research India Private Limited: Current Employment. G:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment.

Monosomy 7 and Co-Occurrent Genomic Aberrations Determine Chemotherapy Response in Acute Myeloid Leukemia (AML) Patients Using the Cellworks Omics Biology Model (CBM): Mycare-021-04

Background: Monosomy 7/Del 7 (-7) or its long arm (del(7q)) is one of the most common cytogenetic abnormalities in pediatric and adult myeloid malignancies, particularly in adverse-risk acute myeloid leukemias (AMLs). In general, (-7) is associated with poor response to induction chemotherapy (PMID 12393746). At the same time, not all patients fare poorly so the ability to identify responders and non-responders remains a high priority. Aim: To predict the response for induction chemotherapy in AML patients with (-7) and identify novel genomic signatures of response and resistance. Methods: Genomic data from 13 consecutive patients with (-7) were analyzed using the Cellworks Omics Biology Model (CBM) to generate patient-specific protein network models. All data was anonymized, de-identified and exempt from IRB review. For each model, disease simulations were performed and patients were segregated into HOXA-upregulated and HOXA-downregulated cohorts based on the simulation levels of HOXA5 and HOXA9. Digital drug simulations for induction chemotherapy were accomplished by measuring the impact of drug effect on a cell growth score, a composite of cell proliferation, viability and apoptosis indices. Each patient-specific model was analyzed to identify mechanisms underlying treatment outcomes. Results: 7/13 (54%) of (-7) patients failed to achieve remission after induction chemotherapy (Table 1) which highlighted that (-7) alone does not confer resistance to chemotherapy. CBM identified other genomic alterations that determine chemotherapy response, including DNA repair deficiency genes, mismatch repair (MMR), and homologous recombination repair (HRR) genes. DNA methylation and histone methylation (H3K27me) impacting HOXA gene expression, mainly HOXA5 and HOXA9, were identified as upstream regulators of DNA repair genes. Loss or reduced levels of EZH2 is associated with lower H3K27 methylation and thereby higher expression of HOXA5 and HOXA9 gene targets. High active levels of HOXA correlated with low rates of successful remission induction (22%, n=7) and lower activity levels of HOXA correlated with successful induction chemotherapy (100%, n=4) (Table 1). CBM identified that (-7) results in a decreased expression of EZH2, CARD11, EIF3, PMS2, HUS1, KMT2C (MLL3), CDK5 and IKZF1 genes. Since EZH2 abnormalities alone are not implicated in poor prognosis for AML patients, we sought other aberrations that prevent HOXA upregulation. Using CBM, we identified multiple accompanying aberrations which regulate HOXA genes. Deletions of KAT6A, ASXL1, DNMT3B, DNMT3L genes and high KMT2A-partial tandem duplication correspond to HOXA-upregulation whereas EED amplification, gain of function mutations in DNMT3A, mutations in IDH1/2, MYC and KAT6A amplification and KDM4A deletion result in HOXA-downregulation. Conclusion: Alterations of chromatin regulation have consequences for transcription factors that regulate expression of DNA repair genes. Under conditions where DNA repair is enhanced, induction chemotherapy was 78% less likely to effect remission in (-7) AML patients undergoing induction chemotherapy. Loss of H3K27 methylation associated with loss of PRC2 function by any means resulted in HOXA-upregulation and upregulation of DNA repair genes induced resistance to induction therapy. On the other hand, CBM analysis identified genetic signatures associated with a 100% remission rate from AML induction therapy despite the presence of (-7). Generation of H3K27me caused by PRC2 activation resulting from numerous mechanisms led to HOXA-downregulation and 100% response to induction therapy. Stratification of patients harboring (-7) by HOXA biomarker analysis could inform treatment planning, avoid drug-related adverse events and reduce treatment costs after validation with a larger prospective dataset. Disclosures Castro: Cellworks Group Inc: Consultancy. Watson:Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kumar:Cellworks Research India Private Limited: Current Employment. Nair:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Mohapatra:Cellworks Research India Private Limited: Current Employment. G:Cellworks Research India Private Limited: Current Employment. Agarwal:Cellworks Research India Private Limited: Current Employment. Suseela:Cellworks Research India Private Limited: Current Employment. Ganesh:Cellworks Research India Private Limited: Current Employment. Sauban:Cellworks Research India Private Limited: Current Employment. Kumar:Cellworks Research India Private Limited: Current Employment. Raman:Cellworks Research India Private Limited: Current Employment. Singh:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Lunkad:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Howard:Servier: Consultancy, Other: Speaker; Boston Scientific: Consultancy; Sanofi: Consultancy, Other: Speaker; EUSA Pharma: Consultancy; Cellworks: Consultancy.

Assessment of Cellworks Omics Biosimulation Therapy Response Predictions for Patients with Acute Myeloid Leukemia (AML) Using Cellworks Singula™: Mycare-020-01

Background. In addition to clinical considerations (e.g., age, de novo vs secondary disease, comorbidities), therapy selection for AML patients is often based on information considering only cytogenetics and/or molecular aberrations and ignoring other patient-specific omics information that could potentially enable selection of more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification, the current overall outcome of AML patients remains relatively poor. The Cellworks Singula™ report predicts clinical response to physician-prescribed treatments using the novel Cellworks Omics Biology Model (CBM) that simulate in silico downstream molecular effects on cell signaling and survival of drug treatments in patient-specific diseased cells. Methods. The performance of Singula™ was evaluated in a cohort of 474 AML patients aged 2 to 85. The pre-defined Singula™ Classifier utilizes individual patients' next-generation sequencing (NGS) profiles to provide a dichotomous prediction of response or non-response to the physician prescribed treatments. The clinical outcome data for these subjects, i.e., complete response (CR) and overall survival (OS), were obtained from the TCGA and other 144 PubMed publications, each including also information on patients' cytogenetics, targeted gene mutations, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized the cytogenetic and molecular data to generate a Singula™ predicted response (i.e., CR vs non-response) classification for each patient. Statistical analyses, including assessments of accuracy, sensitivity, specificity, and negative (NPV) and positive predictive (PPV) values were performed to compare the Singula™ predicted clinical response to the actual observed clinical response. Kaplan-Meier curves, associated log rank tests and median OS are provided for patients stratified by Singula™ predicted response. Multivariate Cox proportional hazards regression was used to further test the hypothesis that Singula™ is an independent predictor for OS once adjusted for patient age and actual prescribed treatment. Results. Data are summarized in Table 1. The Singula™ classifier had 92.3% (90.6%, 95.3%) accuracy in predicting correctly observed patient complete response to the prescribed treatment. with 97.3% (95.0%, 98.8%) sensitivity. Singula™ had 83.3% (76.1%, 89.1%) specificity for the non-responder patients (n=138; 29.1%). For each of the non-responders, Singula™ provided an alternative treatment therapy predicted to produce clinical response. Assuming at least 2% of the non-responders would have responded to the alternative Singula™ prescribed treatment, Singula™ improves CR rates compared to the original physician prescribed treatment (McNemar's p-value < 0.05). Figure 1 provides the Kaplan-Meier curves of Singula-predicted responders vs non-responders for a subset of 292 subjects that had OS data available. In multivariate Cox proportional hazards models, the Singula Classifier remained a significant predictor of overall survival (HR = 2.171, p-value < 0.0001) once adjusted for patient age and physician prescribed treatment. Conclusions. Cellworks Singula™ has high accuracy and sensitivity in predicting CR for AML patient. Singula also has high specificity in identifying patients who are unlikely to respond physician and may prescribed potentially effective therapies. The Singula™ predicted responders have a significantly longer OS than the predicted non responders. Thus, Cellworks Singula™ can accurately predict AML response, be used to validate or reject a physician's therapy selection decision and, eventually, provide alternative treatment recommendations. Disclosures Marcucci: Novartis: Speakers Bureau; Abbvie: Speakers Bureau; Iaso Bio: Membership on an entity's Board of Directors or advisory committees; Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial). Watson:Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Amara:Cellworks Research India Private Limited: Current Employment. Pampana:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Stein:Stemline: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau.

Immunogenicity and safety of the first indigenously developed Indian tetravalent influenza vaccine (split virion) in healthy children (6 months to 17 years of age): a randomized, multicenter, phase III clinical trial

ABSTRACT This phase III clinical trial was conducted to evaluate the immunogenicity and safety of the Tetravalent Influenza Vaccine (Split virion) I.P. (TetIV), containing two strains each of influenza A and B, developed indigenously in the country for the first time by M/s Cadila Healthcare Limited, India for use in the pediatric population (6 months −17 years of age), and compare it to that of a licensed seasonal Trivalent Influenza Vaccine (TriIV) of Sanofi Pasteur India Private Limited, containing two influenza A and one influenza B strains. Three hundred six subjects of either sex, 6 months to 17 years of age, were randomized in a 1:1 ratio to receive either TetIV or TriIV. Immunogenicity assessments (antibodies against A/H1N1, A/H3N2, B/Phuket, and B/Brisbane) were performed using the hemagglutination inhibition assay at baseline and 28 days after the last vaccination. TetIV was found to fulfill the criteria set by the United States Food and Drug Administration on the requirements of clinical data for licensure of seasonal inactivated influenza vaccines for the pediatric population. The seroconversion rates with TetIV were 94.6% for A/H1N1, 93.9% for A/H3N2, 91.2% for B/Brisbane, and 87.2% for B/Phuket strains. TetIV showed non-inferiority and superiority in immune response, as compared to TriIV, against the shared strains and an additional B strain, respectively. Both the vaccines were tolerated well by all the study participants, and an addition of the fourth strain in TetIV did not compromise the safety as compared to that of TriIV. The most common adverse event reported in both groups was fever.

CBCT use to Evaluate Vital Mandibular Inter-Foramin Anatomical Structures

Background: The aim of the study was to evaluate the vital anatomical structures in the mandibular inter foramin region and to investigate the presence of sexual dimorphism with respect to the left and right sides region using CBCT. Materials & Method: A total of 60 CBCT scans (30 male & 30 female) were analysed for the MF position & shape, presence and measurement of AL & MIC (both in mm), patterns of emergence of mandibular canal, symmetry of MF & AL. All the scans were taken by CS 9300 (Care stream Health India Private Limited) CBCT machine adjusted at 80 kVp, 15mA, Voxel size 0.3x0.3x0.3 and field of view (FOV) of 10x5 (mandible only). The acquired images were reconstructed into multiplane views (axial, panoramic and cross-sectional) for evaluation. Results: Position 4 of MF (below the apex of second premolar) was most common on right side while position 3 (between first & second premolar) on left side, with 75% of symmetrical MF position. The prevalence of MIC was noted in 93.75% of the patients with mean length of 12.09±5.95 mm. The prevalence of AL was 53.13% with mean length of 1.07±1.42mm. Conclusion: The present study recommends a CBCT evaluation of inter-foraminal anatomical structures before planning the placement of implants. However, no sexual dimorphism was found regarding these parameters.

172-LB: Risk of Major Congenital Malformations, Perinatal or Neonatal Death with Insulin Detemir Compared with Other Basal Insulins in Pregnant Women with Preexisting Diabetes: The EVOLVE Study

Aim: The EVOLVE study examined the risk of major congenital malformations and perinatal or neonatal deaths when using insulin detemir (IDet) versus other basal insulins in pregnant women with pre-existing diabetes. Materials and Methods: A prospective, non-interventional, multinational study in pregnant women with type 1 or type 2 diabetes treated with IDet or other insulin treatment. In the present analysis, 727 women using IDet during pregnancy were compared with 730 women using other basal insulin, mainly insulin glargine. The primary endpoint was the number of women completing ≥22 weeks of gestation without any of the following events: major congenital malformations, perinatal or neonatal deaths. Results: At enrolment 86% of subjects had type 1 diabetes (mean age: 31 years; BMI: 26 kg/m2) and mean A1C was 7.1%. There was no difference between treatment groups in crude or adjusted risk difference for pregnancies without major congenital malformations, perinatal or neonatal deaths (Table). Conclusion: In pregnant women with pre-existing diabetes, IDet was not associated with excess risk of major congenital malformations, perinatal or neonatal deaths vs. other basal insulin. Disclosure E.R. Mathiesen: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Novo Nordisk A/S. Speaker’s Bureau; Self; Lilly Diabetes, Novo Nordisk A/S, Sanofi-Aventis. A. Alibegovic: Employee; Self; Novo Nordisk A/S. L.N. Husemoen: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. P. Kelkar: Employee; Self; Novo Nordisk Service Centre India Private Ltd. D.R. McCance: None. H.W. de Valk: None. P. Damm: Advisory Panel; Self; Novo Nordisk A/S. Funding Novo Nordisk A/S

Efficiency in waste collection markets: Changing relationships between firms, informal workers, and the state in urban India

Although recent scholarship has provided rich accounts of waste management privatization in urban India, the origins of the policy models that informed privatization remain unexplored. Further, the place of informal workers in the history of waste management policy and programs is more complicated than that provided by linear accounts of a transition from informal to formal in the existing scholarship. In contrast to existing explanations of these shifts, this paper draws attention to the rise of efficiency as a core municipal concern that explains the shifting relationship arrangements between the state, the informal private sector, and the formal private sector in waste collection markets. To address their concerns with cost of service delivery, Indian policy-makers justified privatization by indirectly drawing upon the influential work of E.S. Savas, the American economist credited with empirically substantiating the theory of efficiency gains from privatization in waste collection markets. Yet, informal systems are in practice not only more efficient than formal ones, they also conform well to Savas’ policy prescriptions for structuring waste collection markets. Efficiency could thus serve as a basis for securing informal workers’ claims as legitimate market participants.

Evaluation of the stability of measles vaccine out of the cold chain under extended controlled temperature conditions

Measles outbreaks occur periodically in remote and difficult to reach areas in countries such as the Democratic Republic of Congo. The possibility to keep measles vaccines at temperatures outside the cold chain for a limited period prior to administration would be an advantage for organizations such as Médecins Sans Frontières, which repeatedly respond to measles outbreaks in difficult contexts.Using stability data at 37 °C and 40 °C provided by Serum Institute of India Private Limited we applied the product release model for Extended Controlled Temperature Conditions (ECTC) to evaluate the possibility of an out of the cold chain excursion.Measles vaccine in the lyophilized form remains above the minimum required potency at the end of the shelf-life for up to 6 days at 37 °C or for 2 days at 40 °C.This evaluation supports the use of a monodose presentation of measles vaccine in ECTC. This could be an advantage for outbreak response in isolated and difficult to reach areas. However the operational advantages of this approach need to be established.

Human Resource Management Techniques Effects on the Adoption of Total Quality Management in the Private Health Care Sector

Whole quality management and human resource management techniques among health care professionals and their union in Haryana, India's private hospitals are the focus of this research. This study's goals are to provide a framework for comprehensive quality management, with an emphasis on the most effective human resource management techniques. The research also intends to look at how HRM practices affected the success of TQM implementation and how HRM practices affected employee satisfaction after TQM was put in place. In terms of both employment and income, India's health care businesses have grown to become a major force in the country. The healthcare industry has several obstacles, but one of the most significant is meeting the demands of its workers while simultaneously maintaining high quality and uniform standards.

The Politics of Industrial Displacement: Evidence from Special Economic Zones

How do politicians locate industrial projects, such as special economic zones and industrial townships, that have highly localized costs (population displacement) and benefits (jobs and infrastructure)? I argue that risk-averse politicians minimize the costs of displacement for industrial projects by locating the projects in areas where they have little existing support. In order to maximize the benefits of the projects, politicians also locate the projects far from state or national borders to ensure that the future benefits of the projects accrue only to potential voters. To test this argument, I geocode the locations of public and private special economic zones in India and use private zones as a control group for public zones. The analysis finds support for the argument in that public zones are significantly more likely to be located in constituencies where the government performed badly in prior elections and far from state and national borders.

Productivity enhancement in engine assembly using lean tools and techniques

Lean assembling is bound together with a framework that is involved with a lot of ways of thinking, rules, instruments and strategies, which whenever forced, take out critical burn through and loss of time in all business formats for constant enhancement. But very scarce explorations about lean manufacturing implementation have been done in automobile industry. This paper represents the productivity enhancement using basic lean manufacturing tools in engine assembly at Renault Nissan Automotive India Private Limited Coimbatore. This paper highlights a methodology developed for standardization and improvement in the process of engine assembly activities using lean manufacturing tools and techniques line by using DMAIC approach. Productivity enhancement is the primary goal which is to be achieved for any profitable manufacturing system. All this initiated by performing study on the manual operator’s activities. For an engine assembly processes the tools description, process description and existing sheets were studied which provided detailed information about all the movements of assembly activities.

The Effect of Phase I Therapy on the Clinical Parameters, VSC Levels, and RBS Levels in Chronic Periodontitis Patients With Diagnosed Diabetes.

ABSTRACTIntroduction:The relationship between chronic periodontitis and type 2 diabetes mellitus (DM) is bidirectional. Halitosis or oral malodor has an effect on psychological and social life of persons, and is seen in individuals with diabetes.Aims and Objectives:The aim of this study was to find out the effect of phase I therapy on the clinical parameters, volatile sulfur compound (VSC) levels, and random blood sugar (RBS) levels in chronic periodontitis patients with diagnosed DM.Materials and Methods:Our study included 80 patients with diabetes and chronic periodontitis. We collected subgingival plaque samples at 1 week and 1 month after scaling and root planing. The parameters measured were probing pocket depth and clinical attachment level for all the teeth at four sites per each tooth. RBS levels were recorded for all the patients. Malodor was measured with Tanita Breath Checker (Tanita India Private Limited, Mumbai, Maharashtra, India).Results:We found a statistically significant reduction in clinical parameter levels, VSC levels, and N-benzoyl-DL-arginine-2-naphthylamide (BANA) levels in both the groups from baseline to 4 weeks with highest levels in diabetic chronic generalized periodontitis (CGP) and lowest in nondiabetic CGP at baseline. The mean intergroup comparison of BANA levels was statistically significant at all intervals of time between the two the groups.Conclusion:There is a significant correlation observed between oral malodor levels, RBS, and clinical parameters in the diabetic group.

Fractional Substitute of Fine Aggregates with Pozzocrete Foundary Sand

To pass on immaterial effort concrete by mixing different degrees of fine total and bond with utilized foundry sand and Pozzocrete to decrease trade and sullying issues in light of utilized foundry sand and Pozzocrete. Pozzocrete P60 is a dealt with worth guaranteed fly slag, researched for its utilization as an inadequate swap for bond in cement (1:1.48:3.21). The usage of Pozzocrete P60 as bond substitution material in cement or as included substance in strong shows different focal points from sensible, explicit and ordinary perspectives. The creative use of utilized foundry sand in solid plans as a fine total substitution material was endeavored as a decision rather than standard cement. This paper demonstrates the results of the solid of blend proportion1:1.48:3.21 in which security is for the most part supplanted with PozzocreteP60 as 10% by weight of bond, and fine hard and fast isn't completely supplanted with utilized foundry sand as 10%, 30% and half by weight of fine total. Five courses of action of blend degrees were made. First (A0) were standard blend (without Pozzocrete and utilized foundry) sand with ordinary fine total (sand) and coarse total and the second (B0) blend contained 10% Pozzocrete P60obtained from DIRK India Private Limited, Nasik, Maharashtra state. Different blends (B1, B2, and B3) contained Pozzocrete P60 (10%) despite foundry sand (10%, 30%and half) solely got from ferrous and non-ferrous metal hurling associations. The compressive quality and water support has been gotten with halfway superseding of Pozzocrete P60 with bond and foundry sand with fine total. Test outcomes demonstrate the augmentation in the quality properties of cement and decreasing water assimilation of cement up to 10% overriding of security with Pozzocrete plus30% supplanting of fine total with utilized foundry sand for quality at 7, 14 and 28 days. Moreover it might be used in non-essential parts with the low range compressive quality where quality isn't required and negligible exertion brief structure is prepared.

Fixed Assets and Inventory Analysis with Reference to Ford India Private Limited

Fixed Assets are the benefits held with the goal of being utilized on persistent reason for thepurpose of delivering or giving products or benefits and are not held for resale in the typical course ofbusiness. Valuation of fixed resources is critical to have reasonable proportion of benefit or misfortune and financialposition of the worry and is intended to be for more years. [1],[ 3],[5] Extent assessment is the connection of subtleties in the spending outlines of a business. Extent assessment is used to survey different issues with a component, for instance, its liquidity, profitability of exercises, and advantage. It is profitable particularly to process the Trend line. This assessment in like manner contains design examination. [2 ],[ 4],[6] Stock proportionality is the goal of intrigue driven stock organization. The fundamental perfect outcome is to have a comparative number of long stretches of stock accessible over all things with the objective that the period of miss the mark on all things would be synchronous. The discretionary goal of stock proportionality is stock minimization. [7],[ 9] ,[11] Through coordinating exact interest estimating with stock administration, replenishmentinventories can be planned to arrive in the nick of time to renew the item bound to runout first, while simultaneously offsetting the stock supply of all items to make their inventories progressively corresponding, and in this way closer to accomplishing the essential objective. The EOQ done in this venture demonstrates the degree of inventories that is utilized for creation and the estimation of the inventories. The ABC approach expresses that, when checking on stock, an organization should rate things from A to C, putting together its evaluations depending with respect to specific principles. This is additionally clarified in the Data Analysis area of this task. [19],[21],[23]

Comparing Performance of Equity, Balanced and Debt Mutual Funds – Empirical evidences from India

In India, one of the broad categorizations of mutual funds is as - equity, balanced, and debt funds, each catering to specific expected return and risk-appetite of investors. Further, it is generally believed that among the aforesaid three categories of funds, Equity funds provide highest returns, followed by balanced funds and debt funds in the given order. However, the risk involved in equity funds is also the higher as compared balanced and debt funds. This paper attempts to empirically compare the returns and risk involved in the aforesaid three broad categories of mutual funds operating in the India over three, five, and ten years time periods. For this, we select three independent samples (of size 60) in each category, namely, equity, balanced, and debt fund. Selection of funds in each category is as per researcher defined criteria. The data on selected schemes is collected from the databases of ‘Value Research India Private Limited’, and AMFI. Measures like annualized returns, standard deviation of returns, Sharpe ratio, and expense ratio are employed to compare the three categories. Hypotheses tests are performed employing single factor ANOVA and Tukey’s HSD test. Based on the evidence gathered, it is observed that over all the three chosen time durations, equity funds have on an average provided superior returns than balanced and debt funds, however, equity funds were also observed to be much more risky than the balanced and debt funds. Therefore for investors ready to take risks in lieu of higher returns, equity funds should be chosen. On the other hand investors who want to play safe with their investments, either balanced or debt funds should be their investment avenues.