The limits of relational governance: Sales force strategies in the U.S. medical device industry

Research Summary: We explore how inter-organizational relationships shape firm boundary decisions. Using data on 545 U.S. medical device manufacturers’ product portfolios and sales governance choices (i.e., internal or external sales forces) from 1983 to 1996, we find relational capital between manufacturers and external sales forces influences future firm boundary decisions. Relational capital lowers the likelihood of integrating the sales function, but only when firms remain focused on the same product market. Further, launching an innovative product has a nuanced effect. For firms lacking relational capital, innovation increases the likelihood of sales integration. This pattern reverses as relational capital accumulates, but only when innovations are in the firm’s existing focal product market. Our findings suggest important limits on the effect of relational governance on firm strategy. Managerial Abstract: Choosing between in-house or external sales is a key strategic decision. In the medical device industry, this decision is particularly important because sales people are conduits between R&D and customers. For firms who initially choose external sales, the tradeoff between maintaining existing links (via external sales) and developing new, direct relationships (by bringing sales in-house) can change significantly as product portfolios change. Analyzing 545 U.S. medical device manufacturers from 1983 to 1996, we find that existing relationships with external sales forces reduce the likelihood of bringing sales in-house, but only when firms remain in the same product market, such as orthopedic implants. When firms launch products in new markets, especially innovations, they are more likely to bring sales in-house

The COVID‐19 Yorkshire Rehabilitation Scale (C19‐YRS): application and psychometric analysis in a post‐COVID‐19 syndrome cohort

As our understanding of the nature and prevalence of post-coronavirus disease 2019 (COVID-19) syndrome (PCS) is increasing, a measure of the impact of COVID-19 could provide valuable insights into patients' perceptions in clinical trials and epidemiological studies as well as routine clinical practice. To evaluate the clinical usefulness and psychometric properties of the COVID-19 Yorkshire Rehabilitation Scale (C19-YRS) in patients with PCS, a prospective, observational study of 187 consecutive patients attending a post-COVID-19 rehabilitation clinic was conducted. The C19-YRS was used to record patients' symptoms, functioning, and disability. A global health question was used to measure the overall impact of PCS on health. Classical psychometric methods (data quality, scaling assumptions, targeting, reliability, and validity) were used to assess the C19-YRS. For the total group, missing data were low, scaling and targeting assumptions were satisfied, and internal consistency was high (Cronbach's α = 0.891). Relationships between the overall perception of health and patients' reports of symptoms, functioning, and disability demonstrated good concordance. This is the first study to examine the psychometric properties of an outcome measure in patients with PCS. In this sample of patients, the C19-YRS was clinically useful and satisfied standard psychometric criteria, providing preliminary evidence of its suitability as a measure of PCS

The self-report version and digital format of the COVID-19 Yorkshire Rehabilitation Scale (C19-YRS) for Long Covid or Post-COVID syndrome assessment and monitoring

The C19-YRS was the first scale reported in the literature for patient assessment and monitoring in Long Covid or Post-COVID syndrome. The scale has demonstrated content validity in a previous COVID-19 follow-up study. The growing number of patients with Post-COVID syndrome required the development of a self-report version (and a digital format) so that the scale can be completed by patients themselves. Individuals with Long Covid and clinicians providing care were involved in iterative changes to the scale. The self-report version of the scale captures symptom severity, functional disability and global health status. The C19-YRS digital format comprises a smartphone application for the patient and a web portal for the clinician to assess, triage and monitor patients remotely. The items have been shown to span all the components of the WHO ICF Framework for health condition

The modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) patient-reported outcome measure for Long Covid or Post-COVID-19 syndrome

Background The C19-YRS is the literature's first condition-specific, validated scale for patient assessment and monitoring in Post-COVID-19 syndrome (PCS). The 22-item scale's subscales (scores) are symptom severity (0–100), functional disability (0–50), additional symptoms (0–60), and overall health (0–10). Objectives This study aimed to test the scale's psychometric properties using Rasch analysis and modify the scale based on analysis findings, emerging information on essential PCS symptoms, and feedback from a working group of patients and professionals. Methods Data from 370 PCS patients were assessed using a Rasch Measurement Theory framework to test model fit, local dependency, response category functioning, differential item functioning, targeting, reliability, and unidimensionality. The working group undertook iterative changes to the scale based on the psychometric results and including essential symptoms. Results Symptom severity and functional disability subscales showed good targeting and reliability. Post hoc rescoring suggested that a 4-point response category structure would be more appropriate than an 11-point response for both subscales. Symptoms with binary responses were placed in the other symptoms subscale. The overall health single-item subscale remained unchanged. Conclusion A 17-item C19-YRSm was developed with subscales (scores): symptom severity (0–30), functional disability (0–15), other symptoms (0–25), and overall health (0–10)

ECOG-ACRIN EAZ171: Prospective Validation Trial of Germline Predictors of Taxane-Induced Peripheral Neuropathy in Black Women With Early-Stage Breast Cancer

PURPOSE: Black women experience higher rates of taxane-induced peripheral neuropathy (TIPN) compared with White women when receiving adjuvant once weekly paclitaxel for early-stage breast cancer, leading to more dose reductions and higher recurrence rates. EAZ171 aimed to prospectively validate germline predictors of TIPN and compare rates of TIPN and dose reductions in Black women receiving (neo)adjuvant once weekly paclitaxel and once every 3 weeks docetaxel for early-stage breast cancer. METHODS: Women with early-stage breast cancer who self-identified as Black and had intended to receive (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel were eligible, with planned accrual to 120 patients in each arm. Genotyping was performed to determine germline neuropathy risk. Grade 2-4 TIPN by Common Terminology Criteria for Adverse Events (CTCAE) v5.0 was compared between high- versus low-risk genotypes and between once weekly paclitaxel versus once every 3 weeks docetaxel within 1 year. Patient-rated TIPN and patient-reported outcomes were compared using patient-reported outcome (PRO)-CTCAE and Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity. RESULTS: Two hundred and forty of 249 enrolled patients had genotype data, and 91 of 117 (77.8%) receiving once weekly paclitaxel and 87 of 118 (73.7%) receiving once every 3 weeks docetaxel were classified as high-risk. Physician-reported grade 2-4 TIPN was not significantly different in high- versus low-risk genotype groups with once weekly paclitaxel (47% v 35%; P = .27) or with once every 3 weeks docetaxel (28% v 19%; P = .47). Grade 2-4 TIPN was significantly higher in the once weekly paclitaxel versus once every 3 weeks docetaxel arm by both physician-rated CTCAE (45% v 29%; P = .02) and PRO-CTCAE (40% v 24%; P = .03). Patients receiving once weekly paclitaxel required more dose reductions because of TIPN (28% v 9%; P < .001) or any cause (39% v 25%; P = .02). CONCLUSION: Germline variation did not predict risk of TIPN in Black women receiving (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel. Once weekly paclitaxel was associated with significantly more grade 2-4 TIPN and required more dose reductions than once every 3 weeks docetaxel

Turning high-throughput structural biology into predictive inhibitor design

A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein–ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein–ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein–ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property–free knowledge base for future anticoronavirus drug discovery

Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study

BACKGROUND: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. METHODS: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. RESULTS: 1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. CONCLUSIONS: Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients. FUNDING: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. CLINICAL TRIAL NUMBER: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701

Enabling equitable and affordable access to novel therapeutics for pandemic preparedness and response via creative intellectual property agreements

The COVID-19 pandemic demonstrated that the current purely market-driven approaches to drug discovery and development alone are insufficient to drive equitable access to new therapies either in preparation for, or in response to, pandemics. A new global framework driven by equity is under negotiation at the World Health Organization to support pandemic preparedness and response. Some believe that the global intellectual property (IP) system itself is part of the problem and propose a purely Open Science approach. In this article, we discuss how existing IP frameworks and contractual agreements may be used to create rights and obligations to generate a more effective global response in future, drawing on experience gained in the COVID Moonshot program, a purely Open Science collaboration, and the ASAP AViDD drug discovery consortium, which uses a hybrid, phased model of Open Science, patent filing and contractual agreements. We conclude that ‘straight to generic’ drug discovery is appropriate in some domains, and that targeted patent protection, coupled with open licensing, can offer a route to generating affordable and equitable access for therapy areas where market forces have failed. The Extended Data contains a copy of our model IP policy, which can be used as a template by other discovery efforts seeking to ensure their drug candidates can be developed for globally equitable and affordable access