Identifying Novel Leads Using Combinatorial Libraries: Issues and Successes

Chemically generated libraries of small, non-oligomeric compounds are being widely embraced by researchers in both industry and academia. There has been a steady development of new chemistries and equipment applied to library generation so it is now possible to synthesize almost any desired class of compound. However, there are still important issues to consider that range from what specific types of compounds should be made to concerns such as sample resynthesis, structural confirmation of the hit identified, and how to best integrate this technology into a pharmaceutical drug discovery operation. This paper illustrates our approach to new lead discovery (individual, diverse, drug-like molecules of known structural identity using a simple, spatially addressable parallel synthesis approach to prepare Multiple Diverse as well as Universal Libraries) and describes some representative examples of chemistries we had developed within these approaches (preparation of bis-benzamide phenols, thiophenes, pyrrolidines, and highly substituted biphenyls). Finally, the manuscript concludes by addressing some the present concerns that still must be considered in this field

Mesoscale simulations of the November 25-26 and December 5-6 cirrus cases using the RAMS model

The Regional Atmospheric Modeling System (RAMS), developed at Colorado State University, was used during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) 2 (13 Nov. through 6 Dec. 1991) to provide real time forecasts of cirrus clouds. Forecasts were run once a day, initializing with the 0000 UTC dataset provided by NOAA (Forecast Systems Laboratory (FSL) Mesoscale Analysis and Prediction System (MAPS)). In order to obtain better agreement with observations, a second set of simulations were done for the FIRE 2 cases that occurred on 25-26 Nov. and 5-6 Dec. In this set of simulations, a more complex radiation scheme was used, the Chen/Cotton radiation scheme, along with the nucleation of ice occurring at ice supersaturations as opposed to nucleation occurring at water supersaturations that was done in the actual forecast version. The runs using these more complex schemes took longer wall clock time (7-9 hours for the actual forecasts as compared to 12-14 hrs for the runs using the more complex schemes) however, the final results of the simulations were definitely improved upon. Comparisons between these two sets of simulations are given. Now underway are simulations of these cases using a closed analytical solution for the auto-conversion of ice from a pristine ice class (sizes less than about 50 microns in effective diameter) to a snow class (effective diameters on the order of several hundred microns). This solution is employed along with a new scheme for the nucleation of ice crystals due to Meyers et al and Demott et al. The scheme is derived assuming complete gamma distributions for both the pristine and snow classes. The time rate of change of the number concentration and mass mixing-ratio of each distribution is found by calculating either the flux of crystals that grow beyond a certain critical diameter by vapor deposition in an ice supersaturated regime or by calculating the flux of crystals that evaporate to sizes below that same critical effective diameter

Projecting the combined healthcare burden of seasonal influenza and COVID-19

The overlapping 2020-2021 influenza season and COVID-19 pandemic may overwhelm hospitals throughout the Northern Hemisphere. Using a mathematical model, we project that COVID-19 burden will dwarf that of influenza. If non-pharmacological mitigation efforts fail, increasing influenza vaccination coverage by 30% points would avert 54 hospitalizations per 100,000 people.This work was supported by grant U01IP001136 from the Centers for Disease Control, Titos Handmade Vodka, and the Society for Medical Decision Making COVID-19 Decision Modeling Initiative (UTA20-000825).Dell Medical SchoolIntegrative Biolog

Projecting the Combined Health Care Burden of Seasonal Influenza and COVID-19 in the 2020-2021 Season

Background. In mid-2020, there was significant concern that the overlapping 2020-2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Methods. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020-2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021. Results. Across all scenarios, we projected that the COVID-19 burden would dwarf that of influenza. In all but our lowest transmission scenarios, intensive care units were overwhelmed by COVID-19 patients, with the levels of influenza immunization having little impact on health care capacity needs. Consistent with our projections, sustained nonpharmaceutical interventions (NPIs) in Austin prevented COVID-19 from overwhelming health care systems and almost completely suppressed influenza during the 2020-2021 respiratory virus season. Limitations. The model assumed no cross-immunity between SARS-CoV-2 and influenza, which might reduce the burden or slow the transmission of 1 or both viruses. Conclusion. Before the widespread rollout of the SARS-CoV-2 vaccine, COVID-19 was projected to cause an order of magnitude more hospitalizations than seasonal influenza because of its higher transmissibility and severity. Consistent with predictions assuming strong NPIs, COVID-19 strained but did not overwhelm local health care systems in Austin, while the influenza burden was negligible. Implications. Nonspecific NPI efforts can dramatically reduce seasonal influenza burden and preserve health care capacity during respiratory virus season.Integrative Biolog

Treatment utilization and outcomes in elderly patients with locally advanced esophageal carcinoma: A review of the National Cancer Database

For elderly patients with locally advanced esophageal cancer, therapeutic approaches and outcomes in a modern cohort are not well characterized. Patients ≥70 years old with clinical stage II and III esophageal cancer diagnosed between 1998 and 2012 were identified from the National Cancer Database and stratified based on treatment type. Variables associated with treatment utilization were evaluated using logistic regression and survival evaluated using Cox proportional hazards analysis. Propensity matching (1:1) was performed to help account for selection bias. A total of 21,593 patients were identified. Median and maximum ages were 77 and 90, respectively. Treatment included palliative therapy (24.3%), chemoradiation (37.1%), trimodality therapy (10.0%), esophagectomy alone (5.6%), or no therapy (12.9%). Age ≥80 (OR 0.73), female gender (OR 0.81), Charlson-Deyo comorbidity score ≥2 (OR 0.82), and high-volume centers (OR 0.83) were associated with a decreased likelihood of palliative therapy versus no treatment. Age ≥80 (OR 0.79) and Clinical Stage III (OR 0.33) were associated with a decreased likelihood, while adenocarcinoma histology (OR 1.33) and nonacademic cancer centers (OR 3.9), an increased likelihood of esophagectomy alone compared to definitive chemoradiation. Age ≥80 (OR 0.15), female gender (OR 0.80), and non-Caucasian race (OR 0.63) were associated with a decreased likelihood, while adenocarcinoma histology (OR 2.10) and high-volume centers (OR 2.34), an increased likelihood of trimodality therapy compared to definitive chemoradiation. Each treatment type demonstrated improved survival compared to no therapy: palliative treatment (HR 0.49) to trimodality therapy (HR 0.25) with significance between all groups. Any therapy, including palliative care, was associated with improved survival; however, subsets of elderly patients with locally advanced esophageal cancer are less likely to receive aggressive therapy. Care should be taken to not unnecessarily deprive these individuals of treatment that may improve survival

Projecting Need for a COVID-19 Alternative Care Site (ACS) Austin, TX

To support the city of Austin and Travis County in responding to the threatening rise in COVID-19 hospitalizations, we used a data-driven model of COVID-19 transmission in the Austin-Round Rock MSA to project hospitalizations until February 4th, estimate the risk that cases will exceeding local capacity, and determine effective triggers for opening an alternative care site (ACS) to expand capacity. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19 and do not represent the full range of uncertainty. Rather, they are meant to provide plausible scenarios for COVID-19 healthcare demand and inform decisions that balance the high costs of establishing an ACS with the risks of outstripping local healthcare capacity.Integrative Biolog

COVID-19 alert stages, healthcare projections and mortality patterns in Austin, Texas, May 2021

To support public health decision-making in Austin, Texas, we project COVID-19 healthcare demand as vaccines continue to roll out, and we provide retrospective estimates for in-hospital COVID-19 mortality during surge and non-surge periods of the pandemic. The projections indicate that a return to COVID-19 Alert Stage 2 in May 2021 would be unlikely to cause a healthcare surge that exceeds local ICU capacity. However, our retrospective estimates of in-hospital COVID-19 mortality suggest that even modest surges may increase the COVID-19 fatality rate and that, throughout the pandemic, in-hospital mortality has disproportionately occurred in communities with overlapping socioeconomic, occupational, and health risks. The analyses are based on multiple assumptions about the transmission rate, age-specific severity of COVID-19, and efficacy of vaccines, and thus do not represent the full range of uncertainty that the city of Austin may encounter. We are posting these results prior to peer review to provide insights regarding changing COVID-19 risks as vaccination coverage continues to increase and to guide the relaxation of COVID-19 mitigation measures in the spring and summer of 2021.Integrative Biolog

Impact of Social Distancing Measures on Coronavirus Disease Healthcare Demand in Central Texas, USA

Social distancing orders have been enacted worldwide to slow the coronavirus disease (COVID-19) pandemic, reduce strain on healthcare systems, and prevent deaths. To estimate the impact of the timing and intensity of such measures, we built a mathematical model of COVID-19 transmission that incorporates age-stratified risks and contact patterns and projects numbers of hospitalizations, patients in intensive care units, ventilator needs, and deaths within US cities. Focusing on the Austin metropolitan area of Texas, we found that immediate and extensive social distancing measures were required to ensure that COVID-19 cases did not exceed local hospital capacity by early May 2020. School closures alone hardly changed the epidemic curve. A 2-week delay in implementation was projected to accelerate the timing of peak healthcare needs by 4 weeks and cause a bed shortage in intensive care units. This analysis informed the Stay Home-Work Safe order enacted by Austin on March 24, 2020.Dell Medical SchoolIntegrative Biolog

Effects of Cocooning on Coronavirus Disease Rates after Relaxing Social Distancing

As coronavirus disease spreads throughout the United States, policymakers are contemplating reinstatement and relaxation of shelter-in-place orders. By using a model capturing high-risk populations and transmission rates estimated from hospitalization data, we found that postponing relaxation will only delay future disease waves. Cocooning vulnerable populations can prevent overwhelming medical surges.Dell Medical SchoolIntegrative Biolog