New drug clinical trials, whether successful or failed, are likely to have errors. From a statistical point of view, there are two types of errors: Type I and Type II. The Type I error, also known as a false-positive error, occurs when an ineffective drug shows positive results, suggesting that the drug in question is efficacious for treating the indicated disease or condition. A Type I error is most concerning to regulatory authorities who strive to keep ineffective or harmful drugs from the market. The Type II error, also known as a false-negative error, occurs when an effective drug does not show positive results, suggesting that the drug in question is ineffective for treating the indicated disease or condition. A Type II error is most concerning to the sponsors of the trial because of the very real likelihood of keeping an effective drug from providing a return on their research investments. This report suggests statistical methods to effectively control the Type I error and minimize the Type II error in the clinical trials of new drugs.