对用于罕见病药物重定向的表型数据进行丰富分析
Alberto Ambesi-Impiombato1, Kimberly Cox1, Sylvie Ramboz1
1PsychoGenics, Paramus, NJ, United States.
Frontiers in pharmacology
|August 10, 2023
概括
药物诱导的行为特征分析 (DBSA) 有效地确定了罕见疾病的潜在治疗方法. 蒂安尼在逆转亨廷顿病方面表现有前途.
科学领域:
- 计算生物学是一种计算生物学.
- 神经科学是一个神经科学.
- 药理学 药理学是指药理学的学科.
背景情况:
- 药物诱导行为特征分析 (DBSA) 是一种机器学习方法,用于in silico化合物选.
- DBSA分析了体内行为数据,以识别可能逆转疾病症状并帮助药物发现的药物.
- 罕见疾病存在重大未满足的医疗需求,需要新的药物发现方法.
研究的目的:
- 评估药物诱导行为特征分析 (DBSA) 作为一种用于罕见疾病药物发现的系统方法.
- 在亨廷顿病小鼠模型中评估批准药物的治疗潜力,以逆转行为症状.
- 通过对有前途的候选药物的体内测试来验证DBSA预测.
主要方法:
- 将DBSA应用于来自SmartCube®自动化体内表型化平台的高内容行为数据.
- 选了数十种已批准的药物用于Q175异合的敲进小鼠的表型逆转,这是亨廷顿病模型.
- 通过测试tianeptine in vivo对急性和慢性影响的疗效来验证DBSA预测.
主要成果:
- 对于已知可以治疗亨廷顿病症状的药物,DBSA预测得到了丰富,包括布洛普,莫达菲尼尔,甲基,SSRI和蒂安尼.
- 在体内测试证实,蒂安尼在Q175小鼠中显著挽救了行为表型.
- 该方法在识别罕见疾病的症状缓解治疗方面表现有希望.
结论:
- 药物诱导行为特征分析 (DBSA) 是一种可行的目标不可知方法,用于在罕见疾病药物发现中产生假设.
- DBSA提供了一种替代方法,用于确定高负担和未满足需求的疾病的治疗方法.
- 这项研究验证了DBSA作为一种强大的工具,用于在罕见的神经疾病中重新定位和发现药物.
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