Neurodegenerative diseases (NDDs) are incurable and debilitating conditions that result in progressive degeneration and/or death of nerve cells in the central nervous system (CNS). Identification of viable therapeutic targets and new treatments for CNS disorders and in particular, for NDDs is a major challenge in the field of drug discovery. These difficulties can be attributed to the diversity of cells involved, extreme complexity of the neural circuits, the limited capacity for tissue regeneration, and our incomplete understanding of the underlying pathological processes. Drug discovery is a complex and multidisciplinary process. The screening attrition rate in current drug discovery protocols mean that only one viable drug may arise from millions of screened compounds resulting in the need to improve discovery technologies and protocols to address the multiple causes of attrition. This has identified the need to screen larger libraries where the use of efficient high-throughput screening (HTS) becomes key in the discovery process. HTS can investigate hundreds of thousands of compounds per day. However, if fewer compounds could be screened without compromising the probability of success, the cost and time would be largely reduced. To that end, recent advances in computer-aided design, in silico libraries, and molecular docking software combined with the upscaling of cell-based platforms have evolved to improve screening efficiency with higher predictability and clinical applicability. We review, here, the increasing role of HTS in contemporary drug discovery processes, in particular for NDDs, and evaluate the criteria underlying its successful application. We also discuss the requirement of HTS for novel NDD therapies and examine the major current challenges in validating new drug targets and developing new treatments for NDDs.

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, or COVID-19) has been detrimental to human health, economy, and wellbeing. Little information is known on the epidemiology and outcome of the disease in a localized community within Iraq. We carried out an audit of confirmed cases of COVID-19 in the Kirkuk General Hospital. Data from the 20th of June to the 31st of July, 2020, were collected and analyzed. Suspected COVID-19 cases were confirmed by real-time polymerase chain reaction (RT-PCR). Data on clinical symptoms, age, and treatment protocols were analyzed concerning the outcome. Our study included a total of 200 individual confirmed COVID-19 patients. The majority of cases 55% (n = 110) displayed severe symptoms, while 32.5% (65 cases) and 12.5% (25 cases) of patients displayed moderate to mild symptoms, respectively. The rate of death in the referred patients was 5%. Most patients admitted to the hospital for treatment recovered and were discharged from the hospital within 5 to 30 days post-diagnosis. Statistical analysis revealed that patients treated with oseltamivir, hydroxychloroquine, and azithromycin in combination with vitamins C and D have shorter hospital stay compared to patients receiving the same therapeutic protocol in combination with steroids. Moreover, a higher mortality rate (4.5%) was observed in patients treated with oseltamivir, hydroxychloroquine, ceftriaxone, and steroids. This study highlights a significant relationship between age, secondary ailments, and the choice of medications as simple predictors of the outcome of COVID-19.

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