基因毒性杂质及其警示结构
【医药】如何控制基因毒性杂质
01、何为基因毒性杂质基因毒性杂质（或遗传毒性杂质，Genotoxic Impurity，GTI）是指能直接或间接损害DNA，引起DNA突变、染色体断裂、DNA重组及DNA 复制过程中共价键结合或插入，导致基因突变或癌症的物质（如卤代烷烃、烷基磺酸酯类等）。
潜在基因毒性杂质（Potential Genotoxic Impurity ，PGI）结构中含有与基因毒性杂质反应活性相似的基团（如肼类、环氧化合物、N-亚硝胺类等），通常也作为基因毒性杂质来评估。
基因毒性杂质主要来源于原料药合成过程中的起始物料、中间体、试剂和反应副产物。
此外，药物在合成、储存或者制剂过程中也可能会降解产生基因毒性杂质。
除此之外，有些药物通过激活正常细胞而产生基因毒性物质导致突变，如化疗药物顺铂等。
02、何为基因毒性杂质“警示结构”由于杂质结构的多样性，一般很难进行归类，因此，在缺乏安全性数据支持的情况下，法规和指导原则采用“警示结构”用来区分普通杂质和基因毒性杂质。
所谓“警示结构”，是指杂质中的特殊基团可能与遗传物质发生化学反应，诱导基因突变或者染色体断裂，因此具有潜在的致癌风险。
对于含有警示结构的杂质，应当进行（Q）SAR预测和体内外遗传毒性和致癌性研究，或者将杂质水平控制在毒理学关注阈值（TTC）之下。
但是含有警示结构并不能说明该杂质一定具有遗传毒性，而确认有遗传毒性的物质也不一定会产生致癌作用。
杂质自身性质和结构特点会对其毒性产生抑制或调节作用。
警示结构的重要性在于它提示了可能存在的遗传毒性和致癌性，为进一步的杂质安全性评价与控制指明方向。
（关于基因毒杂质警示结构的详细信息可参考欧盟发布的警示结构《Development ofstructure alerts for the in vivo micronucleus assay in rodents》）。
03、基因毒性杂质严格控制的必要性基因毒性杂质最主要的特点是在极低浓度时即可造成人体遗传物质的损伤，导致基因突变并促使肿瘤发生。
药物中基因毒性杂质分析方法的研究
药物中基因毒性杂质分析方法的研究2山东辰龙药业有限公司 272300摘要：遗传性的毒素会破坏DNA，使其具有致癌性，具有很大的危险性。
因为它的结构性较强，所以在服用药物时，会有吸收此类杂质的危险。
在一些国家，对有毒物质的限制已成为一种主要的药品进入市场。
本文介绍了遗传毒性杂质的基本概念、相关标准、部分杂质的检测限度，为检测基因毒性杂质提供了理论基础，保证了患者的使用安全。
关键词：药物；基因毒性；杂质检测方法引言药品的安全，并不是由其本身的毒性决定的，而是由其含有的杂质决定的。
有机杂质可引起遗传变异、染色体断裂、重组等。
因其来源广泛、有毒，已严重危害人类健康。
现有的方法已不能满足对微量基因毒性物质的检测需求，因此，如何对其进行高效的分析具有重要的现实意义。
本文介绍了近年来在检测方法、检测极限等方面的研究进展。
为药品中的基因毒性物质的检测与控制提供了基础和基础，确保了用药的安全性。
一基因毒性杂质研究现状1.1基因毒性杂质来源基因毒性杂质是一种常见的药物。
原料、中间体、副产物、助剂、残留剂、贮存不当等都会引起基因毒性。
目前，基因毒性杂质普遍存在，对人体健康构成极大威胁。
因此，要对其进行严格的科学检验，并对其进行定量检测。
Duane和Ambavaram提出，利用评估决策树来决定生产中含有或预期的有害物质的生产工艺。
Duane介绍了在加工过程中，如何使用评价决策树对遗传毒素的影响，从而为制药企业在生产过程中，不能识别出有毒物质的来源，提供了一个明确的思路。
1.2法规对基因毒性杂质的要求以及国内外药典规定现状为避免遗传毒素对患者的伤害，全球的监管机构一直在更新和改进遗传毒素。
美国食品及药物管理局和欧洲食品药品监督管理局的指南均推荐采用与“毒理学关注阈值”相关的限制标准，以控制基因毒性杂质进入制药公司。
TTC是指确定可被接受的化学物质的摄入量。
如果终生服药，TTC估算出每天可吸收的基因毒性杂质不能超过1.5μg。
基因毒性杂质的评估与控制
◆ ICH S9中所定义的晚期癌症用原料药和制剂 ◆ 已上市药物中使用的辅料、调味剂、着色剂和香料 ◆ 药物包材中的可浸出杂质
精品课件
四、ICH M7（上市产品应考虑的问题）
上市后变更——原料药研发、生产、控制
◆范围：包括合成路线、试剂、溶剂、工艺条件发 生变更时，诱变性杂质对潜在风险影响的评估
制剂新上市申报：1）原料药合成变更，导致产生新杂质或已有杂质可接受标准增加； 2）配方变更、组分变更或生产工艺变更，导致产生新的降解产物或已有降解产物可接 受标准增加；3）指征变更或给药方案变更，导致可接受癌症风险水平受到重大影响
◆ 药物合成中首次使用的辅料
不适用于
◆ 以下类型的原料药和制剂：生物/生物技术制品；肽类；寡核苷酸；放射药物；
Leadscope
MultiCASE
NTP PAN Pharma Pendium RTECS ToxNet /ChemID Plus TRACE from BIBRA VITIC from Lhasa Limited
特点 公开，毒性物质及疾病登记，包括危害性评价的毒理学研究资料 公开，包括化学致癌物、结构及试验数据，1985—2011 阶段研究 公开，1980—2011，致癌性数据库 公开，可按结构查询的毒性数据库，包括来自CPDB， ISSCAN 等数据库的信息 公开，欧洲化学品信息 商用，包括Gene-Tox 和CCRIS 公开，美国环保局公布、经专家审评过的3 000 种化学物质的致突变性研究结果 公开，美国国立癌症研究所 公开，国际化学品安全性项目总结 公开，美国环保署用以人群健康风险评价，着重在危害确认及剂量反应关系评价 公开，化学致癌物，包括结构及试验数据 公开，日本现有化学品数据库，包括高生产容量化学品( High production volume chemicals)
基因毒性杂质及其警示结构
基因毒性杂质及其警示结构
据研究，化合物具有基因毒性的原因可能是因为其能够与DNA结合并导致DNA损伤，从而引起基因突变和细胞死亡。
此外，一些化合物也可能会干扰细胞的DNA修复机制，从而进一步加剧其基因毒性。
在药品生产过程中，如何控制基因毒性杂质的含量？
为了控制基因毒性杂质的含量，药品生产企业需要采取一系列措施，包括选择合适的原料和反应条件、对反应过程进行严格监控、采用有效的分离和纯化技术、以及对最终产品进行全面的质量控制等。
此外，药品生产企业还需要对基因毒性杂质进行全面的风险评估，并制定相应的控制策略，以确保药品的安全性和有效性。
最后，基因毒性杂质的控制不仅是药品生产企业的责任，也需要相关监管机构的支持和监督。
只有通过全社会的共同努力，才能保障药品的安全性和有效性，为人民群众的健康保驾护航。
___夫妇在19世纪70年代对化合物致癌机理进行了深入研究，并提出了“亲电理论”。
该理论指出，构成DNA的四个碱基中存在许多亲核位点，如嘧啶环和嘌呤上的N和O等，这些位点可以与亲电试剂反应，从而引起基因突变，是诱发癌症的重要原因。
___在19世纪80年代提出了致癌性的警示结构（SAs）的概念，这些结构含有的化合物与DNA发生作用的可能性较高，可能诱发癌症。
___的相关机构在2009年的报告中收录了三十余种基因毒性警示结构，这些结构的具体信息也在报告中列举了出来。
基因毒性杂质培训 PPT课件
对甲苯磺酸季戊酯（布洛芬）： 苯：溶剂石油醚可能含有苯
右旋布洛芬中可能含有的基因毒性杂质
右旋布洛芬中合成路线
甲苯中要控制苯！
布洛芬赖氨酸中可能含有的基因毒性杂质
布洛芬赖氨酸合成工艺
=
布洛芬赖氨酸水杨醛的限度问题
台湾2016年9月缺陷信及回复：
氟马西尼合成工艺
氟马西尼中N,N-二甲苯胺基因毒性
盐酸格拉司琼中可能含有的基因毒性杂质
Granisetron起始原料1-甲基吲唑-3-羧酸 中可能含有的基因毒性杂质
Granisetron起始原料氮杂壬胺可能含有的基因毒性杂质
盐酸格拉司琼中可能含有的基因毒性杂质
盐酸格拉司琼欧洲药品质量管理局(EDQM) 缺陷信
磷酸氟达拉滨中可能含有的基因毒性杂质
Fludarabine起始原料合成工艺
磷酸氟达拉滨合成工艺
氯苄
氯苄的毒性资料
The Carcinogenic Potency Database (CPDB)致癌物数据库公布的1547种致癌物质中有氯苄：
托拉塞米中可能含有的基因毒性杂质
托拉塞米起始原料合成工艺
O
O NH2 A Carbamates 氨基甲酸类
AA NN
AR Hydrazines and azo Compounds 肼和偶氮化合物
EWG
Michale-reactive Acceptors 迈克尔加成反应受体
O P
OR
O S
OR
Alkyl Esetrs of Phosphonates or Sulfonates 膦酸酯或者磺酸酯
D-（+）-樟脑磺酸乙酯
基因毒性杂质(genotoxic
TTC用于计算未做研究的化学物质的接触量，这些 化学物质不会有明显的致癌性或者其他毒性。
ConcentrationLimit ( ppm) TTC (ug / day) dose(g / day)
TTC理论不可以应用于那些毒性数据（长期研究） 充分的致癌物质，也不可以做高风险毒性物质的风 险评价。
TTC是一个风险管理工具，它使用的是概率方法。所以 TTC不能被理解为绝对无风险的保障。
TTC
意思是：假如有一个基因毒性杂质，并且我们对 它的毒性大小不了解，如果它的每日摄入量低于 TTC值，那么，该基因毒性杂质的致癌风险将不 会高于100000分之一的概率。
某些特定情况，TTC值高于1.5μg/day也是可以 接受的。比如药物的短期接触，即治疗某些声明 预期在5年以下的某些严重疾病，或者这种杂质是 一种已知物质，人类在其他方式上对它的摄入量 会更高（比如在食品上）。这个需要根据实际情 况再进行推算。
应该有合理的分析方法去检测和量化这些杂质的 残留量。
毒理学研究
为一个不存在阀值的基因毒性致癌物定义一个安 全的摄入量水平（零风险观点）是不可能的，并 且从活性药物成分中完全的除去基因毒性杂质经 常是很难做到。这样就要求我们建立一个可接受 的风险水平，例如对一个低于可忽略风险的每日 摄入量进行评价。
判断是否为基因毒性杂质
通过Carcinogenic potency database (CPDB) 数据库查询，数据库中现有1574种致癌物质的列 表。链接 /chemnamein dex.html ，还可查询到关于基因毒性方面研究 的出版物。
基因毒性杂质卤代烃的风险评估
有数据表明氯乙烷、氯甲烷为基因毒性杂质，因 此有理由怀疑其他低分子卤代烃类也有类似的作 用。在生产中应该对其进行相应的控制。
基因毒性杂质(genotoxic
风险：（体内）基因毒性物质在任何摄入量水平上对DNA 新当药被合 磺成酸、酯原或料相纯关化物、质储所存污运染输了（的与磺包酸装作物为接起触始）物等料过用程于都药可物能活产性生成基分因时毒，性是杂否质能保证药物活性成分中潜在基因毒性杂质不超过其 都有潜在的破坏性，这种破坏可能导致肿瘤的产生。但不 TTC值？应当要考虑各种烷基或芳基取代磺酸酯杂质的累加风险。
氨基糖甙类抗生素：大剂量、长期使用会引起耳毒性；
尽管无数据表明这些酯对人的毒性影响，然后依然有上述基因毒性物质以杂质的形式存在于含磺酸酯类药物活性成分的药品中的潜在
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用药时间与毒性杂质限度
含有多个基因毒性杂质的评估
EMA： 结构不同的，单个杂质的限度应小于1.5ug/day. 结构相似的，总的基因杂质限度定为1.5ug/day.
FDA（和EMA类似）： 单个杂质造成的癌症风险机率应该小于100000分 之一； 有相同作用机制的结构相似的杂质，其含量总和 应该参考TTC值进行评估。
1、PGLs (potentially genotoxic impurities有潜在基因毒性的杂质)
azoxy(氧化能偶氮说基) “不存在明显的阀值，或是任何的摄入水平都具有致 癌的风险”。 基因毒性杂质磺酸盐的风险评估
有相同作用机制的结构相似的杂质，其含量总和应该参考TTC值进行评估。 如果无structural alert是否可足够说明该杂质不存在基因毒性？
基因毒性杂质介绍及检测方法
基因毒性杂质介绍及检测⽅法1什么是基因毒性杂质基因毒性杂质（或遗传毒性杂质，Genotoxic Impurity ，GTI）是指化合物本⾝直接或间接损伤细胞DNA，产⽣基因突变或体内诱变，具有致癌可能或者倾向。
潜在基因毒性的杂质（Potential Genotoxic Impurity ，PGI）从结构上看类似基因毒性杂质，有警⽰性，但未经实验证明的黄曲霉素类、亚硝胺化合物、甲基磺酸酯等化合物均为常见的基因毒性杂质，许多化疗药物也具有⼀定的基因毒性，它们的不良反应是由化疗药物对正常细胞的基因毒性所致，如顺铂、卡铂、氟尿嘧啶等。
2为何着重研究基因毒性杂质基因毒性物质特点是在很低浓度时即可造成⼈体遗传物质的损伤，进⽽导致基因突变并可能促使肿瘤发⽣。
因其毒性较强，对⽤药的安全性产⽣了强烈的威胁，近年来也越来越多的出现因为在已上市药品中发现痕量的基因毒性杂质残留⽽发⽣⼤范围的医疗事故，被FDA强⾏召回的案例，给药⼚造成了巨⼤的经济损失。
例如某知名国际制药巨头在欧洲市场推出的HIV蛋⽩酶抑制剂维拉赛特锭（Viracept， mesylate)，2007 年7⽉，EMA暂停了它在欧洲的所有市场活动，因为在其产品中发现甲基磺酸⼄酯超标，甲基磺酸⼄酯是⼀种经典的基因毒性杂质，该企业为此付出了巨⼤的代价，先内部调查残留超标的原因，因在仪器设备清洗时⼄醇未被完全清除⽽残留下来，与甲基磺酸反应形成甲基磺酸⼄酯。
在被要求解决污染问题后还被要求做毒性研究，以更好的评估对患者的风险。
同时有多达25000 名患者暴露于这个已知的遗传毒性。
直到解决了这所有问题后 EMA才恢复了它在欧洲的市场授权。
近年来各国的法规机构如ICH、FDA、EMA等都对基因毒性杂质有了更明确的要求，越来越多的药企在新药研发过程中就着重关注基因毒性杂质的控制和检测。
3哪些化合物是基因毒性杂质杂质的结构多种多样，对于绝⼤多数的杂质⽽⾔，往往没有充分的毒性或致癌研究数据，因⽽难以对其进⾏归类。
关于药物中的基因毒性杂质
关于药物中的基因毒性杂质众所周知，药物并⾮纯净物质，其在⽣产贮运过程中常常会引⼊或产⽣“杂质”，⽽由于杂质的存在，⼜往往会带来潜在的安全性问题，所以科研⼈员通常需要在充分研究的基础上对杂质加以有效控制。
⽽基因毒性杂质危害性⼤，需要严格控制其在药物中的限度，保障⽤药安全。
基因毒性杂质的检测⾯临杂质种类多和化学性质活泼等问题，分析⽅法复杂多样，从⽽对药物中基因毒性杂质的检测⽅法提出了很⾼的要求。
⼀、基因毒性杂质基因毒性杂质( genotoxic impurity，GTI) 定义为“经过适当遗传毒性实验模型，如细菌基因突变( Ames) 实验，证实具有遗传毒性的杂质”。
其主要包括PGLS( potentially genotoxic impurities有潜在基因毒性的杂质)和GTLs( genotoxic impurities基因毒性杂质)两种。
基因毒性杂质可能从基因突变、染⾊体畸变、DNA 损伤与修复等⼏个⽅⾯同DNA 发⽣直接或间接的相互作⽤，从⽽改变DNA 结构与构象或引起DNA 的损伤，进⽽影响DNA的功能或改变其遗传特性，最终引起突变、癌变、畸变等遗传毒性。
新药合成、原料纯化、储存运输〔与包装物接触)等过程都可能产⽣基因毒性杂质，故⽽，近年来药审机构及研发⼈员对其愈发关注!各国药品监督管理部门对药物中基因毒性杂质的控制出台了⼀系列的指导⽂件，旨在严格控制该类杂质在药物中的限度。
⼆、有关基因性杂质的参考指南1.EMEA（欧洲药品管理局）2000年，欧洲监管机构率先开始关注基因毒性杂质，Pharm Europa发表了⼀篇⽂章，提到注意在成盐⼯艺中，磺酸在⼄醇溶液中形成磺酸酯的潜在风险。
2002年，专利药物委员会(CPMP，现为⼈⽤药物委员会CHMP)发布了⼀份关于基因毒性杂质的意见书，指南中将基因毒性杂质的限度根据有⽆阈值分为两类。
2006年⾸先颁布了《基因毒性杂质限度指南》,并⾃2007年1⽉1⽇起正式实施。
基因毒性杂质-基毒、重金属资料
遗传毒性杂质遗传毒性：泛指各种因素（物理、化学因素）与细胞或生物体的遗传物质发生作用而产生的毒性。
1、致突变性：与DNA相互作用产生直接潜在的影响，使基因突变（bacteria reverse mutation（Ames）试验）2、致癌性：具有致癌可能或倾向（需要长期研究！）3、警示结构特征：一些特殊的结构单元具有与遗传物质发生化学反应的能力，会诱导基因突变或者导致染色体重排或断裂，具有潜在的致癌风险。
遗传毒性物质：在很低的浓度下即可诱导基因突变以及染色体的断裂和重排，因此具有潜在的致癌性。
EMA通告（1）、具体事项：1、哪些品种中会出现甲磺酸酯（或甲磺酸烷基酯）。
特别是甲磺酸盐等形式的API或其合成中用到甲磺酸的API，甲磺酸烷基酯-甲磺酸甲酯、乙酯、其它低级醇酯，应认定为潜在杂质。
2、羟乙基磺酸盐、苯磺酸盐、对甲苯磺酸盐的API。
应说明类似物质磺酸烷基酯或芳基酯污染的危险。
3、限度要求：无其它毒性数据时，这些高风险杂质应依据TTC设定限度。
1.5μg÷以g为单位的最大日剂量得ppm限度。
4、法律依据：EP专论要求凡以甲磺酸盐和羟乙基磺酸盐形式存在的API，均应在其生产过程中采取以下安全措施：必须对生产工艺进行评估以确定家磺酸烷基酯（羟乙基磺酸烷基酯）形成的可能，特别是反应溶媒含低级醇的时候，很可能会出现这些杂质。
必需时需对生产工艺进行验证以说明在成品中未检出这类杂质。
（2）、落实措施：1、API生产是否涉及在甲磺酸（羟乙基磺酸盐、苯磺酸盐、对甲苯磺酸等低分子量磺酸）或相应酰氯存在下，使用甲醇、乙醇、正丙醇、异丙醇等低级脂肪醇（如甲醇、乙醇、正丙醇、异丙醇等）。
2、对相应酯形成的可能性是否降到最低。
3、是否有有效的清除精制步骤。
设备清洗-是否设计的低级脂肪醇的使用（方法，TTC限度）？起始物料（低分子量磺酸盐或酰氯）中是否控制了其低级脂肪醇酯（方法，TTC限度）？当被磺酸酯或相关物质污染的磺酸用于API合成时能否保证其中潜在的遗传毒性杂质不超过TTC？应考虑各种烷基或芳基磺酸酯杂质累积的风险。
基因毒性杂质培训PPT演示幻灯片
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甲磺酸伊马替尼中可能含有的基因毒性杂质
33
伊马胺：
甲磺酸伊马替尼起始原料合成工艺
伊马酸：
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甲磺酸伊马替尼合成工艺
35
米力农中可能含有的基因毒性杂质
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米力农起始原料合成工艺
米力农起始原料有4-甲基吡啶、乙酰氯、原甲酸三乙酯以及氰乙酰胺，目前没有这几个起始原料的合成工艺。
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布洛芬合成路线
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布洛芬中具有结构警示的杂质
3-氯-2,2-二甲基-1-丙醇
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布洛芬中基因毒性杂质的讨论
2-氯丙酸 3-氯-2,2-二甲基-1-丙醇 1，3-二氯-2,2-二甲基丙烷
对甲苯磺酸季戊酯（布洛芬）：
苯：溶剂石油醚可能含有苯
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右旋布洛芬中可能含有的基因毒性杂质
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右旋布洛芬中合成路线
27
醋酸阿比特龙中可能含有的基因毒性杂质
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醋酸阿比特龙加拿大缺陷信1/1（2018.5）
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Continued!
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醋酸阿比特龙起始原料合成工艺
3-吡啶硼酸合成工艺： 31
醋酸阿比特龙合成工艺
Mesityl oxide is a by-product which is originated from the aldol condensation of acetone to give diacetone alcohol 丙酮缩合成二丙酮醇，二丙酮醇脱水生成异亚丙基丙 酮 （2ppm)：
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甲溴后马托品起始原料扁桃酸的合成路线
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甲溴后马托品起始原料托品醇的合成路线 见前述！
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甲溴后马托品的合成路线
基因毒性杂质之结构警示(欧洲)
EUR 23844 EN -2009Development of structural alerts for the in vivo micronucleus assay inrodentsRomualdo Benigni a , Cecilia Bossa a , Olga Tcheremenskaia aand Andrew Worthb aIstituto Superiore di Sanita’, Environment and Health Department,Rome, Italy b Institute for Health & Consumer Protection, European Commission -Joint Research Centre, Ispra, ItalyThe mission of the IHCP is to provide scientific support to the development and implementation of EU policies related to health and consumer protection.The IHCP carries out research to improve the understanding of potential health risks posed by chemical, physical and biological agents from various sources to which consumers are exposed.European CommissionJoint Research CentreInstitute for Health and Consumer ProtectionContact informationAddress: TP 582E-mail: andrew.worth@ec.europa.euTel.: +39 0332 789566Fax: +39 0332 786717http://http://ecb.jrc.ec.europa.eu/qsar/http://ec.europa.eu/dgs/jrc/Legal NoticeNeither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of this publication.A great deal of additional information on the European Union is available on the Internet.It can be accessed through the Europa serverhttp://europa.eu/JRC 52274EUR23844 ENISSN 1018-5593Luxembourg: Office for Official Publications of the European Communities© European Communities, 2009Reproduction is authorised provided the source is acknowledgedPrinted in ItalyABSTRACTIn vivo mutagenicity and carcinogenicity studies are posing a high demand for test-related resources. Among these studies, the micronucleus test in rodents is the most widely used, as follow up to positive in vitro mutagenicity results. A recent survey of the (Q)SAR models for mutagenicity and carcinogenicity has indicated that no (Q)SAR models for in vivo micronucleus are available in the public domain. Therefore, the development and extensive use of estimation techniques such as (Q)SARs, read-across and grouping of chemicals, promises to have a huge animal saving potential for this endpoint. In this report, we describe the identification of structural alerts for the in vivo micronucleus assay, and provide the list of underlying chemical structures. These structural alerts provide a coarse-grain filter for the preliminary screening of potential in vivo mutagens.LIST OF ABBREVIATIONSEPA Environmental Protection AgencyEU European UnionFDA Food and Drug AdministrationHOMO Highest Occupied Molecular OrbitalISS Istituto Superiore di Sanita’JRC Joint Research CentreLUMO Lowest Unccupied Molecular OrbitalOECD Organisation for Economic Cooperation and Development(Q)SAR(Quantitative)Structure-Activity RelationshipREACH Registration Evaluation and Authorisation of CHemicalsROC Receiver Operating CurveSA Structural AlertSA_BB Benigni-Bossa structural alerts for mutagnicity /carcinogenicity in ToxtreeSA_Mic Structural alerts refers for the in vivo micronucleus assay inToxtreeSA_Prot Structural alerts for protein binding in the OECD QSAR ToolboxCONTENTS1.Introduction (6)2.Structural alerts (8)3.Development of structural alerts for the in vivo micronucleus assay (10)4. Final considerations (20)5.References (21)Appendix 1 (23)1.IntroductionMutagenicity testing is an important part of the regulatory hazard assessment of chemicals. It is undertaken for two main reasons: a) to detect chemicals that might cause genetic damage in germ cells, and thus increase the burden of heritable (genetic) disease in the human population; and b) to detect chemicals that might be carcinogenic (based on the assumption that mutagenesis, for example in somatic cells, is a key event in the process of carcinogenesis). Since no method is able alone to detect all possible genotoxic events, a wide array of test systems has been developed and accepted internationally in regulatory schemes.Most often, these methods are used within a 2-tiered integrated testing approach: Tier 1 includes in vivo assays, and Tier 2 includes in vivo assays. As a matter of fact, mutagenicity testing was the first toxicity endpoint for which in vivo assays were accepted for regulatory testing, some 25 years ago. The latter usually comprise bacterial mutagenicity and cytogenetics tests, although gene mutation testing in cultured mammalian cells is sometimes also undertaken.Tier 2 of the testing strategy involves the use of short-term in vivo studies (usually a bone-marrow cytogenetics assay) to assess whether any potential for genotoxicity detected at the Tier 1 in vivo stage is actually expressed in the whole animal. Thus, negative results in vivo are usually considered sufficient to indicate lack of mutagenicity, whereas a positive result is not considered sufficient to indicate that the chemical represents a mutagenic hazard (i.e. it could be a false positive). The above approach to genotoxicity testing has been adopted throughout the EU1,and has been recommended internationally as part of the strategy for predicting and quantifying mutagenic and carcinogenic hazard (Ashby et al.,1996; Combes et al.,2007; Kirkland and Speit,2008; Lilienblum et al.,2008).1http://guidance.echa.europa.eu/docs/guidance_document/information_requirements_r7a_en.p df?vers=20_08_08According to an assessment carried out by the former European Chemicals Bureau (ECB), the in vivo mutagenicity studies, shortly followed by carcinogenicity, are posing high demand for test-related recourses (Pedersen et al.,2003; Van der Jagt et al.,2004). Among those, the micronucleus test in rodents is the most widely used, as follow up to positive in vivo mutagenicity results. A recent survey of the (Q)SAR models for mutagenicity and carcinogenicity (performed jointly by ISS and the JRC) has indicated that no (Q)SAR models for in vivo micronucleus are available in the public domain (Benigni et al.,2007): therefore, the development and extensive use of estimation techniques such as (Q)SARs, read-across and grouping of chemicals, might have a huge saving potential for this endpoint.In this report, we describe: a) the collection of data on chemicals tested with the in vivo micronucleus assay; b) preliminary analyses of the data; c) the identification of Structural Alerts (SA) proper to this toxicological endpoint. First, some background information on the concept of SA is provided.2.Structural alertsThe SAs for a toxicological endpoint are molecular functional groups or substructures known to be linked to that type of toxicity.The SAs are a coarse-grained approach to the use of Structure-Activity Relationships (SAR) to understand the toxicity mechanisms and to predict the toxic activity of chemicals. Because of their nature, the SAs have the role of pointing to chemicals potentially toxic, whereas no conclusions or indications about nontoxic chemicals are possible (except by exclusion) (Benigni and Bossa,2006; Benigni and Bossa,2008).A set of chemicals characterized by the same SA constitute a family (class) of compounds that share the same mechanism of action. The reactivity of a SA can be modulated or abolished by the remaining part of the molecule in which the SA is embedded. At a coarse-grain level, such modulating effects can be represented by other molecular substructures (e.g., bulky groups ortho to an aromatic amine group) that are known to have an influence on the reactivity of the SA. Usually, the knowledge on the modulating substructures is quite limited for most of the SAs, thus it provides limited help in deciding which chemicals in a class will actually be toxic and viceversa. A powerful generalization of the Structure-Activity Relationships is provided by the Quantitative Structure-Activity Relationship (QSAR) analysis, which produces a mathematical model that links the biological activity to a limited number of physical chemical or other molecular properties (descriptors) with general relevance. Since most of the descriptors have continuous values, the QSARs provide fine-tuned models of the biological activity,and can give account of subtle differences. General introductions on QSAR are given elsewhere (Hansch and Leo, 1995, Hansch et al.,2002). Thus the SAs are not a discriminant model on the same ground of the QSAR models: the latter produce estimates for both positive and negative chemicals, as well as for the gradation of toxic potency.The main role of the SAs is that of preliminary, or large-scale screenings. They are excellent tools for coarse-grain characterization of chemicals, including: description of sets of chemicals, preliminary hazard characterization, category formation and priority setting (enrichment). Since fine-tuned QSARs do not exist for many types of chemicals, the models based on SAs hold a special place in predictive toxicology. Theknowledge on the action mechanisms as exemplified by the SAs is routinely used in SAR assessment in the regulatory context (see, for example, the mechanistically-based reasoning as presented in Woo et al. (2002). In addition, the SAs are at the basis of popular commercial (e.g., DEREK, by Lhasa Ltd.2) and non-commercial software systems (e.g., Oncologic, by US Environmental Protection Agency[EPA]3).Recently, as follow-up of the collaboration between ISS and JRC,a rulebase for mutagens and carcinogens has been designed and implemented in the software Toxtree 1.51. It uses a structure-based approach consisting of a new compilation of SAs for carcinogenicity and mutagenicity. It also offers three mechanistically based QSARs for congeneric classes (aromatic amines and aldehydes) (Benigni et al., 2008a). Toxtree 1.51 is freely available from the JRC website.42/3/oppt/newchems/tools/oncologic.htm4http://ecb.jrc.ec.europa.eu/qsar/qsar-tools/index.php?c=TOXTREE3.Development of structural alerts for the in vivomicronucleus assay3.1 DataThe compilation of SAs for the in vivo micronucleus assay in rodents provided here, is based on both the existing knowledge on the mechanisms of toxic action and a structural analysis of the chemicals tested in the assay.The in vivo micronucleus data in the public domain is quite limited. A search of the Chemical Carcinogenesis Research Information System(CCRIS) at the Toxnet website with the query: “in vivo micronucleus” points only to 240 chemicals.5For this work, the remarkably larger commercial database by Leadscope Inc., called “FDA SAR Genetox Database” was used.6This database contains more than 700 chemicals tested in in vivo micronucleus with rodents, and includes data from both the public domain and the US Food and Drug Administration (FDA) files. A large majority of data were based on the analysis of micronuclei in bone marrow cells; for details on the technique, see for example, Krishna and Hayashi (2000).3.1 Preliminary analysesSince the main role of the in vivo micronucleus assay in regulatory schemes is that of confirming (or disproving) the positive in vitro results, it is of interest to check how the in vivo micronucleus results relate to the rodent carcinogenicity data and to the primary in vitro prediction test, i.e., the Salmonella typhimurium(Ames) test.Tables I and II display the relationships between the in vivo micronucleus ad the two reference tests. The results for rodent carcinogenicity and the Ames test were retrieved from the freely available ISSCAN v3a database,7which is characterized by:5/cgi-bin/sis/search6/product_info.php?products_id=777http://www.iss.it/ampp/dati/cont.php?id=233&lang=1&tipo=7a) the high quality of both chemical and biological information; b) the QSAR-ready format (Benigni et al.,2008b). Obviously, the total numbers of chemicals in the two tables are relative only to those chemicals tested in both systems.Table I. Contingency table comparing the results of the rodent carcinogenicity testwith the micronucleus testTable II:Contingency table comparing the results of the Salmonella typhimuriumassay with the micronucleus testTable I shows that is the in vivo micronucleus assay is poorly sensitive to the rodent carcinogens: about 60% of the rodent carcinogens are not detected by the micronucleus. The poor sensitivity of the micronucleus assay to potential genotoxins is also apparent from Table II.It should be emphasized that the present results obtained with the large Leadscope micronucleus database are in agreement with previous analyses based on smaller datasets in the public domain (Benigni,1995).In a second round of analyses, the extent to which the micronucleus data are related to well established indicators of DNA and protein binding was checked. This in view of the plethora of the reported mechanisms of micronucleus induction. As a matter of fact, micronuclei are markers of both aneugenic (change in the chromosomes number, usually by loss) and clastogenic (chromosome breakage) effects. It is generally assumed that such effects are generated through a range of different pathways. Evidence (mainly gathered from in vitro studies) indicates that micronuclei can be induced e.g., by typical DNA-attacking agents (e.g., alkylating agents like methylmethane sulfonate), by mitotic spindle poisons (e.g., colcemide, vincristine), or by inhibitors of cytokinesis (e.g., cytochalasin B). The latter effects are probably due to interference with proteins. Other chemicals are thought to be clastogenic through aspecific disturbance of cytokinesis due to lipophilicity (Dorn et al.,2007).The relative influence of DNA and protein binding on micronucleus generation was checked by recording the distribution of structural alerts for the two effects in the Leadscope in vivo micronucleus database. As probes for DNA binding, we used the structural alerts for carcinogenicity / mutagenicity implemented in Toxtree 1.51. As a matter of fact, the large majority of these alerts refer to genotoxic carcinogenicity, which is assumed to be caused through direct interaction with DNA (Benigni and Bossa, 2008). As probes for protein binding, we used the alerts implemented in the Organisation for Economic Cooperation and Development (OECD) QSAR Toolbox.8 These alerts were mainly developed from the mechanistic knowledge on skin sensitization, and model the covalent binding to proteins.The results of the above analysis is displayed in Figure 1 as a ROC graph. It appears that the structural alerts for carcinogenicity /mutagenicity correlate to some extent with the induction of micronuclei, whereas those for protein covalent binding show no correlation (in the graph, they are on the diagonal line which represents random results).8/document/23/0,3343,en_2649_34379_33957015_1_1_1_1,00.htmlFigure 1. Receiver Operating Curve showing the concordance of two sets of structural alerts with the results of the in vivo micronucleus assay(SA_BB refers to the Benigni-Bossa alerts in Toxtree; SA_Prot refers to the alerts for proteinbinding in the OECD QSAR Toolbox)3.3 Structural Alerts for in vivo micronucleus assaySince the above analyses pointed to genotoxic effects as an important determinant of micronuclei induction, we developed the list of Structural alerts for in vivo micronucleus using the carcinogenicity / mutagenicity alerts in Toxtree as a core , and then searching for additional substructures specific to the micronucleus-positive chemicals. From the Toxtree alerts for carcinogenicity / mutagenicity,we excluded four alerts specific for non-genotoxic mechanisms of carcinogenicity.Using linear discriminant analysis as an analytical tool and ROC plots as a graphical tool, a series of additional substructures were added / removed to / from the Toxtreealerts in order to increase sensitivity and specificity.In these exploratory analyses, wescreened the very large collection of substructural patterns and functional groups (more than 27,000) contained in the software Leadscope Enteprise 2.4.15-6. We also re-checked the Toolbox protein binding alerts for individual substructures related with micronucleus induction.The result is the optimized list of alerts in Appendix 1. Together with the Toxtree alerts, it contains five additional substructures identified in the course of this research. For the sake of clarity,the codes of the alerts in Toxtree are maintained, whereas the five additional alerts have new codes.Figure 2 displays the agreement between the alerts for in vivo micronucleus, and the experimental results for this endpoint. Out of 547 negatives, the specificity of the SAs is 0.57. The sensitivity is 0.65 out of 182 positives. The overall accuracy is 0.59. For a comparison, the ROC graph shows the newly developed alerts for micronucleus together with those for DNA and protein binding. It appears that the performance of the final list of alerts is considerably higher than that of the DNA binding and Protein binding alerts.Table III gives the true positive rate for the individual alerts.Figure 2 Receiver Operating Curve showing the concordance of structural alerts for the in vivo micronucleus assay with the experiemtnal results for this assay(SA_Mic refers to the in vivo micronucleus alerts in Toxtree)Table III: Characterisation of Structural Alerts.3.4 Further analyses on the alerts for micronucleusA striking evidence in Table III is the relatively low percentage of true positives identified by many SAs. In other words, often the toxic potential of the alerts is not translated into actual toxicity in the experimental system. For a comparison, the True Positive Rate of the various alerts for mutagenicity /carcinogenicity in Toxtree is remarkably higher, ranging from 70 to 100% (Benigni and Bossa,2008).The above result contributes to better understand the evidence in Tables I and II, where it appears that the micronucleus assay has many more negatives than the carcinogenicity bioassay and the Salmonella mutagenicity test. Table III indicates that the low sensitivity of the micronucleus assay is largely due to the fact that often,chemical functionalities and substructures which are supposed to be reactive do not exert their potential reactivity in this experimental system.The issue of the low sensitivity of the micronucleus assay has been recognized by scientists involved in research aimed at improving the available short-term mutagenicity assays; as a matter of fact, validation of further, more sensitive in vivo assays (e.g., in vivo Comet assay) is presently in progress (Kirkland and Speit,2008).In the context of this research, we investigated if a general effect of bioavailability on the limited sensitivity of micronucleus was apparent. To this aim, we considered two chemical descriptors well known as to be linked to bioavailability: logP (hydrophobicity) and Molar Refractivity (MR) (Hansch and Leo,1995). The two descriptors were calculated with the C-QSAR software (Daylight, Inc.)9for all the chemicals in the micronucleus database. For the two parameters, Table IV reports the ranges of values for positive and negative micronucleus results.Table IV: Ranges of C-logP and C-MR in chemicals assayed withthe micronucleus testIt appears that the micronucleus positives cover a more limited range of logP values than the micronucleus negatives; however, the consideration of exclusion values for logP in combination with the SAs did not improve the overall performance (results not shown).Whereas no general effect of logP (or MR) was found, analyses on the individual chemical classes showed that logP cut-offs can be identified for the classes of Nitroaromatics (Negatives at logP > 0.0), Aromatic Diazo (Negatives at logP < 3.7),9/about/index.htmland Oxolanes (Negatives at logP > 1.5). The consideration of these cut-offs increases the specificity of the SAs from0.57 to 0.60.The above result suggests a possible strategy to understand and modeling the many negative results observed with the micronucleus. Since the bone marrow (main target of the test) is an organ easily accessible by the blood stream, it can be hypothesized that the lack of effect shown by several chemicals with SAs (hence potentially reactive) is due to the many possible targets for reaction encountered in the in vivo situation; this diminishes the probability for the chemicals of reaching, and interacting with the molecular target(s) of the micronucleus test. For example, highly reactive chemicals will probably react with any target encountered in their way (e.g., proteins, water)before reaching the bone marrow. Thus it can be envisaged that QSARs for individual chemical classes should be developed, and that they should consider parameters linked to chemical reactivity(such as HOMO and LUMO energies). It can be hypothesized that the models derived from these QSARs will contribute to modulate the individual SAs.4. Final considerationsStructural alerts point to classes of chemicals with the potential to cause toxic effects (here, in vivo micronucleus). Since this potential is modulated in each molecule by the rest of the structure (e.g., other functional groups, electronic structure, bulky groups), not all chemicals in a class are equally toxic. In the case of the SAs identified in the present study for the in vivo micronucleus test, the percentage of chemicals that have SAs but are not active in the test system is particularly high. This evidence agrees with, and rationalizes the notion that this test system is sensitive to genotoxins to a limited extent, and does not respond to a large number of recognized carcinogens and mutagens. For this reason, a positive in vivo micronucleus result adds a strong weight to an in vivo positive mutagenicity result, whereas a negative in vivo micronucleus result has a much lower relevance. The availability of a wider range of in vivo mutagenicity assays is a priority for the present regulatory strategies.Within the above perspective, the SAs identified in this study provide a coarse-grain filter for a preliminary screening of potentially in vivo mutagens. In a risk assessment process, further information(e.g., QSARs for individual classes, experiments) is necessary to complete this initial screening step.5.ReferencesAshby,J., M.D.Waters, J.Preston, I.D.Adler, G.R.Douglas, R.Fielder, M.D.Shelby,D.Anderson, T.Sofuni, H.N.B.Gopalan, G.Becking and C.Sonich-Mullin(1996). IPCS harmonization of methods for the prediction and quantification of human carcinogenic/mutagenic hazard, and for indicating the probable mechanism of action of carcinogens. Mutat.Res./Fundamental and Molecular Mechanisms of Mutagenesis. 352:153-157.Benigni,R. (1995). Mouse bone marrow micronucleus assay: relationships with in Vitro mutagenicity and rodent carcinogenicity. J.Toxicol.Environ.Health.45:337-347.Benigni,R. and C.Bossa(2006). Structural alerts of mutagens and carcinogens.put.-Aid.Drug Des.2:169-176.Benigni,R. and C.Bossa(2008). Structure Alerts for carcinogenicity,and the Salmonella assay system: a novel insight through the chemical relational databases technology. Mutat.Res.Revs.659:248-261.Benigni,R., C.Bossa, N.G.Jeliazkova, zeva and A.P.Worth(2008a). The Benigni / Bossa rulebase for mutagenicity and carcinogenicity -a module of Toxtree. JRC Report EUR 23241 EN. European Commission Joint Research Centre, Ispra, Italy.http://ecb.jrc.ec.europa.eu/DOCUMENTS/QSAR/EUR_23241_EN.pdfBenigni,R., C.Bossa, A.M.Richard, and C.Yang (2008b). A novel approach: chemical relational databases, and the role of the ISSCAN database on assessing chemical carcinogenicity.Ann.Ist.Super.Sanità. 44:48-56.Benigni,R., C.Bossa, zeva and A.P.Worth(2007).Collection and evaluation of (Q)SAR models for mutagenicity and carcinogenicity. JRC Report EUR 22772 EN. European Commission Joint Research Centre, Ispra, Italy.http://ecb.jrc.ec.europa.eu /documents/QSAR/EUR_22772_EN.pdfCombes,R., C.Grindon, M.T.D.Cronin, D.W.Roberts and J.Garrod(2007). Proposed integrated decision-tree testing strategies for mutagenicity and carcinogenicity in relation to the EU REACH legislation.ATLA. 35:267-287.Dorn,S.B., G.H.Degen, T.Müller, D.Bonacker, H.F.P.Joosten, J.van der Louw,F.A.A.van Acker and H.M.Bolt(2007). Proposed criteria for specific and non-specific chromosomal genotoxicity based on hydrophobic interactions.Mutat.Res./Genetic Toxicology and Environmental Mutagenesis. 628:67-75. Hansch,C., D.Hoekman, A.Leo, D.Weininger and C.D.Selassie(2002).Chem-bioinformatics: comparative QSAR at the interface between chemistry and biology.Chem.Revs.102:783-812.Hansch,C. and A.Leo (1995). Exploring QSAR. 1. Fundamentals and applications in chemistry and biology.American Chemical Society. Washington, D.C.Kirkland,D. and G.Speit(2008). Evaluation of the ability of a battery of three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens III.Appropriate follow-up testing in vivo.Mutat.Res.654:114-132.Krishna,G. and M.Hayashi(2000). In vivo rodent micronucleus assay: protocol, conduct and data interpretation.Mutat.Res.455:155-166.Lilienblum,W., W.Dekant, H.Foth, T.Gebel, J.G.Hengstler, R.Kahl, P.J.Kramer,H.Schweinfurth and K.M.Wollin(2008). Alternative methods to safety studiesin experimental animals: role in the risk assessment of chemicals under the new European Chemicals Legislation (REACH).Regulat.Toxicol.82:211-236.Pedersen,F., J.de Brujin, S.J.Munn and K.Van Leeuwen(2003).Assessment of additional testing needs under REACH. Effects of (Q)SARs, risk based testing and voluntary industry initiatives. JRC report EUR 20863 EN. European Commission Joint Research Centre, Ispra, Italy.http://ecb.jrc.ec.europa.eu/home.php?CONTENU=/DOCUMENTS/REACH/PUBLICATIONS/ Van der Jagt,K., S.J.Munn, J.Torslov and J.de Brujin (2004).Alternative approaches can reduce the use of test animals under REACH. Addendum to the Report "Assessment of addtional testing needs under REACH. Effects of (Q)SARs, risk based testing and voluntary industry initiatives. JRC Report EUR 21405 EN.European Commission Joint Research Centre, Ispra, Italy.http://ecb.jrc.ec.europa.eu/home.php?CONTENU=/DOCUMENTS/REACH/PUBLICATIONS/ Woo,Y.T., i, J.L.McLain, M.Ko Manibusan and V.Dellarco(2002). Use of mechanism-based structure-activity relationships analysis in carcinogenic potential ranking for drinking water disinfection by-products. Environ.Health Perspect.110:75-87.Appendix 1European CommissionEUR 23844 EN–Joint Research Centre –Institute for Health and Consumer ProtectionTitle: Development of Structural alerts for the in vivo micronucleus assay in rodentsAuthor(s): Benigni R, Bossa C, Tcheremenskaia O and Worth A Luxembourg: Office for Official Publications of the European Communities 2009–42pp. –21x 29.7cmEUR –Scientific and Technical Research series –ISSN 1018-5593AbstractIn vivo mutagenicity and carcinogenicity studies are posing a high demand for test-related resources. Among these studies, the micronucleus test in rodents is the most widely used, as follow up to positive in vitro mutagenicity results. A recent survey of the (Q)SAR models for mutagenicity and carcinogenicity has indicated that no (Q)SAR models for in vivo micronucleus are available in the public domain. Therefore, the development and extensive use of estimation techniques such as (Q)SARs, read-across and grouping of chemicals, promises to have a huge animal saving potential for this endpoint. In this report, we describe the identification of structural alerts for the in vivo micronucleus assay, and provide the list of underlying chemical structures. These structural alerts provide a coarse-grain filter for the preliminary screening of potential in vivo mutagens.。
基因毒性杂质控制
② 降解杂质
实际检出杂质：长期稳定性及制剂过程中检出的报告限度以上杂质（ICH Q3A/B ）；
潜在杂质：加速试验及光照试验检出的鉴定限以上杂质，长期未确认。
三、基因毒性杂质的鉴别--警示结构
A为烷烃基、芳香基或H；EWG为吸电子取代基，如氰基、羰基或酯基等。 基因毒性的警示结构不只限于以上所列，进一步了解可参见: 马磊,马玉楠等.遗传毒性杂质的警示结构 .中国新药杂志 ,2014，23(18) :2106~11
理化性质如反应活性，溶解性、挥发性，电离度等分析。
三、基因毒性杂质的控制
方法3：案例1（M7 第24页 case1）
a、中间体X距原料药尚有2步反应，标准定入杂质A，杂质A化学性质稳定； b、将杂质A以不同浓度加入中间体X进行加标试验，达1%水平能持续从原
料药中去除至限度的30%以下； c、中试规模多批次成品杂质A结果低于基于TTC限度的30%以下；
杂质的检测水平及拟定限度不超过参比制剂的测得水平；
(2) The impurity is a significant metabolite of the drug substance. 杂质为原料药的重要代谢物；
(3) The observed level and the proposed acceptance criterion for the impurity are adequately justified by the scientific literature.
三、基因毒性杂质的分类
3、举例如下：
例1：瑞戈非尼(Regorafenib)
加拿大审评报告中，一个中间体Ames结果阳性，大鼠肝慧星致突变试验确立NOEL（无反应剂量 水平），提示每日最大摄入该杂质为0.0027mg/kg，如果体重按50kg计，则摄入量为 0.0027×50=0.135mg；瑞戈非尼日最大用量为160mg，故可推测其标准中该杂质限度为 0.0027×50kg/160=0.084%，即840ppm。（显著大于基于TTC水平的约9ppm限度）
基因(遗传)毒性杂质资料-上传
每日最大剂量 报告限度
鉴定限度
Qualification Threshold* 毒性限度
≤2g /天
0.05%
0.10%或者每天 0.15%或者每天
摄入量1.0mg 摄入量1.0mg
（取最小值）
（取最小值）
＞2g /天
0.03% 0.05%
0.05%
/cber/gdlns/ichq3a.pdf
N-Methylols N-亚甲基醇
N-Nitrosamines N-亚硝基胺
Nitro compounds 硝基化合物
O
A
A
Epoxides 环氧丙烷
H N
A
A
Aziridines 氮丙啶类
O O C (S)
(S) N
Halogen
Propiolactones 环丙酯
N or S Mustards β卤代乙胺
Group 3:Heteroatomic Groups(含杂原子化合物）
A N
A
Aminoaryls and alkylated aminoaryls 芳香胺和烷基取代的芳酰胺
O
O NH2 A Carbamates 氨基甲酸类
AA NN
AR Hydrazines and azo Compounds 肼和偶氮化合物
Class4:AlertRelated to parent
第4类：具有警示结构、与API有关、基因毒性（突 变性）未知的杂质
Class5: No Alerts
第5类：没有警示结构，没有基因毒性（突变性）的 杂质
Group1:Aromatic Groups(芳香族化合物）:
OH N
A
A NA
基因毒杂质警示结构
基因毒杂质警示结构
基因毒性杂质是指具有对基因组产生直接或间接的有害影响的化学物质。
这些物质可能导致基因突变、染色体畸变、基因表达异常等，进而对生物体的遗传物质和遗传信息造成损害。
警示结构是指一些特定化学结构或官能团，它们在分子中存在时可能表明该物质具有基因毒性潜能。
这些警示结构通常与DNA结合、干扰细胞的DNA复制或修复机制等相关。
一些常见的基因毒性杂质的警示结构包括：
1.芳香族环（如苯环）：芳香族环结构可以与DNA发生相互作
用，并导致DNA损伤或突变。
2.互氧化物结构：一些含有羟基或酮基的化合物，如环氧化合
物、过氧化物等，都可以引起DNA链的损伤。
3.亲电性基团：有一定亲电性的基团，如氯、亚硝基等，可以
与DNA中的核苷酸发生加成反应，导致DNA损伤。
4.多环芳香烃：包含多个芳香环的多环芳香烃类化合物，如多
环芳香烃类化合物（PAHs），具有潜在的基因毒性。
警示结构只是一种指示可能存在基因毒性的线索，不能仅凭警示结构来判断一个物质的基因毒性。
实际上，进行基因毒性评估需要综合考虑物质的化学性质、生物活性、暴露途径等因素，并进行相关的实验测试和评估。
基毒杂质的警示结构
基毒杂质的警示结构随着科技的发展和全球化的加速，化学制剂的使用越来越广泛。
然而，在这些化学制剂中，有时会存在一些基毒杂质，它们可能会对人体健康造成危害。
因此，建立一种基毒杂质的警示结构非常必要。
基毒杂质通常指的是一些有害的物质，它们被认为是有害的，因为它们可以通过空气、食物或水传播。
这些物质可能会对人体造成许多不同的健康问题，包括皮肤刺激、呼吸道感染、舌头麻痹等等。
其中一些物质可能会引起癌症或其他重大生命威胁。
为了对这些有害物质进行有效监管，需要建立一个基毒杂质的警示结构。
这个结构应该涵盖以下几个方面：首先，需要建立一个统一的有害物质清单。
这个清单应该包括所有已知的有害物质的名称、化学结构、危害性质和来源。
这个清单应该由专业人士进行制定和维护，以确保其中的信息的准确性和完整性。
其次，需要建立一种有害物质的分类方法。
这个分类系统应该根据这些物质的化学特性和潜在危害程度将它们分为若干类。
这个分类系统将有助于监管机构和公众更好地了解这些物质的危害性，并为采取相应的防护措施提供指导。
第三，需要建立一套标准化的有害物质检测方法。
这个方法应该涵盖物质溶解度、纯度、剂型等方面的测试，并应该由专业人士进行制定和维护，以确保测试结果的准确性和可靠性。
这将有助于监管机构更好地识别有害物质，并监测制药企业、食品生产企业等的生产环节。
最后，需要建立一套标准化的有害物质安全风险防护措施。
这些措施应该包括物质存储和运输规范、生产线和设备洁净度标准、操作员保护措施等。
这将有助于企业、医疗机构等对有害物质的风险进行防范控制，并减少患者和从业人员的健康风险。
总之，建立一个基毒杂质的警示结构对于保障公众健康和全球卫生安全至关重要。
只有实施全面的监管和防控措施，才能避免或减少由有害物质引起的疾病和损害。
基因毒性杂质全面信息资料
No or unknow
Yes
Not tested
Class3:AlertUnrelated to parent
Class5:No Alerts
Class4:AlertRelated to parent
Impurity Genotoxic?1
该杂质是否有 基因毒性？
No
API Genotoxic2
该原料是否有 基因毒性？
No
(Staged)TTC (see Table 1)
PDE(e.g.ICH Q3 appendix 2 reference
整理ppt
Control as an ordinary impurity
20
Step 3:
TTC=1.5微克/天
表1：短期用药推荐容许日摄入量
TTC值
疑似基因毒素 的日摄入量
号，作用部位，TTC值等等一系列信息。 近30年的关于基因毒性方面研究的出版物
（PDF版） 用不同分类方法统计的致癌物质列表。
Standard limits for impurities in APIs API中杂质的标准限度
Maximun
Reporting Identification
Daily Dose1 Threshold2,3 Threshold*
每日最大剂量 报告限度
鉴定限度
≤2g /天
0.05%
0.10%或者每天 摄入量1.0mg
整理ppt
1
1
背景知识介绍
2
杂质与杂质限度
3
确定毒性阈值的步骤
4
最大限度地控制杂质
整理ppt
2
1
背景知识介绍
2
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基因毒性杂质及其警示结构
古语有云：“是药三分毒”。
这句话不管在传统中药还是现代化学药都是基本成立的。
对于化学药来说，在活性药物成分（API）的生产过程中，一些起始物料、中间体、试剂和反应副产物不可避免地作为杂质存在于最终产品中，因此一种药物的安全性不仅决定于它本身的毒性情况，也决定于它所含有的杂质的毒性情况。
根据国际人用药品注册技术要求协调会（ICH）指南，原料药杂质可分为有机杂质（有关物质）、无机杂质及残留溶剂三个主要类别。
而大部分基因毒性（或称为遗传毒性）杂质（Genotoxic Impurities, GTIs）就属于一类特殊的有关物质。
近些年发生过多起由于基因毒性杂质残留而导致的药品召回事件，为确保用药安全，各国及地区的相关组织如欧洲药品管理局（EMA）、美国食品药品管理局（FDA）、国际人用药品注册技术要求协调会（ICH）等相继发布杂质控制的相关规程及指导原则。
2017年6月，原国家食品药品监督管理总局（CFDA）加入ICH，这意味着我国在药品安全方面正式向国际接轨；2019年1月，国家药典委员会官网发布了“关于《中国药典》2020年版四部通则增修订内容（第四批）的公示”，其中就包含有“遗传毒性杂质控制指导原则审核稿（新增）”。
因此对国内药企来说，不管是面对国内市场还是走出国门，对基因毒性杂质的控制都是绕不过的坎。
什么是基因毒性杂质？
根据《中国药典》的相关文件定义，基因毒性杂质是指能引起基因毒性的杂质，包括致突变性杂质和其它类型的无致突变性杂质。
其主要来源于原料药的生产过程，如起始原料、反应物、催化剂、试剂、溶剂、中间体、副产物、降解产物等。
致突变性杂质（Mutagenic Impurities）指在较低水平时也有可能直接引起DNA 损伤，导致DNA 突变，从而可能引发癌症的遗传毒性杂质；而非致突变机制的遗传毒性杂质在杂质水平的剂量下，一般可忽略其致癌风险。
而潜在基因毒性杂质（Potential Genotoxic Impurities，PGIs）是指其结构中含有与基因毒性杂质反应活性相似的化学结构，即警示结构（Structural alerts, SAs），通常也作为基因毒性杂质来评估。
化合物为何具有基因毒性？
Miller夫妇（James A. Miller 和Elizabeth C. Miller）对化合物致癌机理做了深入的研究，在19世纪70年代他们提出了著名的化合物致癌的“亲电理论”。
在构成DNA的四个碱基（A，T，G，C）中，有很多的亲核位点，比如嘧啶环和嘌呤上的N和O等，这些位点可以与亲电试剂（如烷基化试剂、酰基化试剂等）反应而产生不可逆的变化，从而引起基因突变，而基因突变是诱发癌症的重要原因。
基因毒性警示结构有哪些？
在Miller夫妇提出“亲电理论”后，John Ashby在19世纪80年代提出了致癌性的警示结构（Structural alerts，SAs）的概念，含有这些结构的化合物就存在与DNA 发生作用的可能，进而可能诱发癌症。
2009年，欧盟的相关机构的报告中收录了三十余种基因毒性警示结构，具体如下：
在这个报告中，也列举了一些含有这些警示结构的化合物等详细信息
总结：本文简单阐述了基因毒性杂质的概念及其作用机理，展示了一些主要的基因毒性警示结构。
需要注意的是，含有这些警示结构的化合物不一定具有基因毒性，同时确定具有基因毒性也不一定会产生致癌作用。
这些警示结构的意义
在于能够提示化合物可能存在的安全风险，为进一步的杂质安全性评价与控制指明方向。
参考文献
1. 国家药典委员会：遗传毒性杂质控制指导原则审核稿（新增）.
2. R. Benigni , C. Bossa. Mechaisms of chemical carcinogenicity and mutagenicity: a review with implications for predictive toxicology. Chem. Rev., 2011, 111, 2507.
3. E. C. Miller, J. A. Miller. Searches for ultimate chemical carcinogens and their reactions with cellular Macromolecules. Cancer, 1981, 47, 2327.
4. E. C. Miller, J. A. Miller. Machanisms of Chemical Carcinogenesis. Cancer, 1981, 47, 105
5.
5. R. Benigni, C. Bossa, O. Tcheremenskaia, A. Worth. Development of structure alerts for the in vivo micronucleus assay in rodents. JRC Scientific and Technical Reports.。