Exploring the Impact of Study drug on PCOS: Insights from Our Recent Phase III Clinical Study

Exploring the Impact of Study drug on PCOS: Insights from Our Recent Phase III Clinical Study Introduction Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age, characterized by irregular menstrual cycles, hyperandrogenism, and polycystic ovaries. Symptoms include weight gain, acne, hirsutism, and infertility, along with metabolic disturbances like insulin resistance and dyslipidemia Download the Case Study Purpose of the Study To evaluate the efficacy and safety of a Study drug in improving clinical and biological parameters in women with PCOS. The study aimed to determine if the Study drug could alleviate symptoms and enhance the overall quality of life by improving gut health and hormonal balance. What we did? Primary Outcome Measure Change in PCOSQ Score: The study measured the change in the Polycystic Ovary Syndrome Questionnaire (PCOSQ) score from baseline to Day 90 to assess the effectiveness of the Study drug in improving the quality of life for women with PCOS. Secondary Outcome Measures Change in PCOSQ score at intermediate time points. Change in scores assessing physical symptoms like hair growth and acne. Change in blood sugar levels and HbA1c. Change in hormone levels, including FSH, LH, estradiol, and testosterone. Change in lipid profile parameters, such as triglycerides, total cholesterol, LDL, and HDL. Safety Endpoints Number of participants who experienced adverse events and those who discontinued the study drug Conclusion The primary outcome measure showed a significant improvement in the PCOSQ score from baseline to Day 90, indicating the effectiveness of the Study drug in enhancing the quality of life for women with PCOS. Secondary outcome measures demonstrated improvements in various clinical and biological parameters, including hormonal balance, insulin sensitivity, and lipid profiles. Safety endpoints were monitored, with a record of participants who experienced adverse events and those who discontinued the study drug. Contact Us Potential Benefits of Probiotics in Managing PCOS Improved Insulin Sensitivity: Probiotics may help enhance insulin sensitivity, a key factor in managing PCOS. Reduced Inflammation: Probiotics can reduce systemic inflammation, which is often elevated in women with PCOS. Hormonal Balance: By supporting gut health, probiotics might help balance hormones, including reducing excess androgen levels. Weight Management: Certain probiotic strains may aid in weight loss and maintenance, beneficial for many women with PCOS. Mood Regulation: Probiotics may improve mood and reduce anxiety, often associated with PCOS Experience of delivering More than 200+ Studies Under different therapeutic area Team of experience Professionals 40+ programmers With an average of 10+ years of experience Building a joyful client relationship 10+ satisfied clients Through a commitment to quality and trust.

Identifying and Rectifying the Human Error in Randomization Plan

Identifying and Rectifying Human Error in Randomization Plan Introduction In clinical trials, accurate application of randomization is crucial for obtaining reliable results in the analysis of study data. However, human errors can significantly impact outcomes, leading to incorrect conclusions. This case study explores a scenario where human error in randomization led to discrepancies between the mean and standard deviation of glucose levels reported by KITE-Ai and Client analyses.. Download the Case Study Background The data presented in this case study is from a diabetes study, where subjects were randomized to active treatment and placebo groups, focusing on glucose levels. Two tables were created, each containing two columns: SUBJID (subject ID) and Glucose Level. Analyses were conducted simultaneously by KITE-Ai and the Client. However, the mean and standard deviation of glucose levels reported by each team did not match, indicating a potential issue. What we did? Data Analysis The discrepancy was traced back to errors in randomization applied by the Client. Specifically: SUBJID 23 and SUBJID 27 were incorrectly included in Active Treatment arm. SUBJID 28 and SUBJID 31, who were supposed to be part of Active Treatment arm, were excluded. This misallocation of subjects caused incorrect glucose level data to be used in the Client’s analysis, thereby affecting the final computed mean and standard deviation values. *Dummy data used, and image is for representation purpose only. The actual data and visualization remain confidential as a part of the CDA and DECP. Impact of Human Error The incorrect randomization had significant consequences: The mean glucose level reported by KITE-AI-Ai was 120.12, whereas the Client reported 122.75. The standard deviation glucose level reported by KITE-Ai was 34.49071, while the Client reported 35.64846. The inclusion of incorrect subjects (SUBJID 23 and SUBJID 27) in the Client’s analysis introduced erroneous data, resulting in a higher mean value. These discrepancies could lead to incorrect conclusions about the efficacy or safety of the treatment under study. Conclusion This case study highlights the critical importance of accurate randomization in clinical trials. Human errors, such as incorrect subject inclusion, can result in significant discrepancies in data analysis, potentially jeopardizing the validity of the trial’s conclusions. It underscores the need for meticulous data management and rigorous verification processes to minimize the risk of such errors and ensure reliable results. Although the case study is from live studies, actual study data is not used here to protect data privacy and dummy is presented here for illustration.  Contact Us Experience of delivering More than 200+ Studies Under different therapeutic area Team of experience Professionals 40+ programmers With an average of 10+ years of experience Building a joyful client relationship 10+ satisfied clients Through a commitment to quality and trust.