qzmjef 发表于 2024-6-24 13:17:37

量子计算+人工智能,怎么样改变制药业?


    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://mmbiz.qpic.cn/sz_mmbiz_jpg/Z6jSflhablwHCFjyuouPs0eNcsU1Usngl7mJXQfJetkk61OOaiaf1BgpfiaBWF56g1NTZMErXgWCbjZJuIXfFGlA/640?wx_fmt=jpeg&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1&amp;tp=webp" style="width: 50%; margin-bottom: 20px;"></p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">源自</span>:智药局</span></p><span style="color: black;">药企们将<span style="color: black;">营销</span>额的15%用于<span style="color: black;">开发</span>,这一数字占<span style="color: black;">全世界</span>所有行业<span style="color: black;">开发</span>总支出的20%以上。</span><span style="color: black;">所幸的是,<span style="color: black;">昂贵</span>的投资<span style="color: black;">常常</span>与创新连在<span style="color: black;">一块</span>。</span><span style="color: black;">药企们<span style="color: black;">持续</span>寻求改进<span style="color: black;">开发</span>过程的新<span style="color: black;">办法</span>,从<span style="color: black;">初期</span>的计算化学数字<span style="color: black;">工具</span>采用者;<span style="color: black;">日前</span>人工智能正在加速渗透…</span><strong style="color: blue;"><span style="color: black;">而下一个技术,则是量子计算。</span></strong><span style="color: black;">这一技术<span style="color: black;">怎样</span>应用到制药<span style="color: black;">行业</span>?当前的市场化<span style="color: black;">状况</span><span style="color: black;">怎样</span>?药企们又该<span style="color: black;">怎么样</span>提早布局?麦肯锡的这份行业报告值得参考。</span><span style="color: black;"><strong style="color: blue;"><span style="color: black;">01</span></strong></span><span style="color: black;"><strong style="color: blue;">量子计算的天然候选人</strong></span><span style="color: black;"><span style="color: black;">药品</span><span style="color: black;">开发</span>的核心环节是识别和<span style="color: black;">研发</span>有助于治愈<span style="color: black;">疾患</span>的分子,这<span style="color: black;">亦</span><span style="color: black;">寓意</span>着制药是应用量子计算的天然候选人。</span><span style="color: black;">而分子是基于量子<span style="color: black;">理学</span>学的系统,QC能比传统计算更有效地预测和模拟其结构、性质和反应性,<span style="color: black;">乃至</span>是原子水平的相互<span style="color: black;">功效</span>。</span><span style="color: black;">虽然量子计算背后的技术很难直观地理解,但它的影响却<span style="color: black;">更易</span><span style="color: black;">把握</span>:它处理某些类型的计算任务的速度比当今的传统计算机要快得多。</span><span style="color: black;"><span style="color: black;">因此呢</span>,一旦完全<span style="color: black;">研发</span>,QC<span style="color: black;">能够</span>在<span style="color: black;">全部</span><span style="color: black;">药品</span>价值链中<span style="color: black;">增多</span>价值。</span><span style="color: black;"><strong style="color: blue;">02</strong></span><span style="color: black;"><strong style="color: blue;"><span style="color: black;">重点</span>价值在<span style="color: black;">药品</span><span style="color: black;">开发</span></strong></span><span style="color: black;">量子计算机<span style="color: black;">能够</span><span style="color: black;">增多</span>适用于生物机制的计算范围、缩短筛选时间,并清理<span style="color: black;">有些</span><span style="color: black;">科研</span>“死角”,<span style="color: black;">极重</span>节省<span style="color: black;">药品</span><span style="color: black;">发掘</span><span style="color: black;">周期</span>的成本。</span><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablzEvW01YHmyPBOSZFPIKic1Mnl5WB5qLpAXEJJ6WhjOl7U7BibBibOOBaJhGiaIZeoYC6Gg5rCN0Xdymg/640?wx_fmt=png&amp;tp=webp&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1" style="width: 50%; margin-bottom: 20px;"><span style="color: black;">图:QC在生物医药中的<span style="color: black;">重点</span>应用环节</span><span style="color: black;"><span style="color: black;">例如</span>以高精度预测分子特性,使当前的CADD/AIDD<span style="color: black;">工具</span>更加有效;针对<span style="color: black;">目的</span>的多种可能结构并行筛选计算库,以<span style="color: black;">增多</span>确定最佳候选<span style="color: black;">药品</span>的机会。</span><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablzEvW01YHmyPBOSZFPIKic1Mb8DYTPib1mxbgfGC1su4N5e6ymthXMwgE7oa8FQEwQiaWTw14MauNU4w/640?wx_fmt=png&amp;tp=webp&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1" style="width: 50%; margin-bottom: 20px;"><span style="color: black;">图:QC<span style="color: black;">加强</span>型CADD<span style="color: black;">能够</span>改善的<span style="color: black;">详细</span><span style="color: black;">行业</span></span><strong style="color: blue;"><span style="color: black;">长远来看,QC能用<span style="color: black;">设备</span>学习(ML)算法<span style="color: black;">发掘</span>新的结构-属性关系,从而改进假设的生成和验证。</span></strong><span style="color: black;">一旦达到足够的成熟度,便能创建含小分子、肽和抗体等在内的新候选<span style="color: black;">药品</span>库,实现更自动化的<span style="color: black;">药品</span><span style="color: black;">发掘</span><span style="color: black;">办法</span>。</span><strong style="color: blue;"><span style="color: black;"><span style="color: black;">目的</span>识别和验证</span></strong><span style="color: black;">在<span style="color: black;">目的</span>识别过程中,可利用QC预测蛋白质的3D结构,并获取高质量数据;<span style="color: black;">乃至</span>是改进DeepMind<span style="color: black;">研发</span>的AlphaFold。它并未<span style="color: black;">处理</span>蛋白质复合物的形成、蛋白质-蛋白质相互<span style="color: black;">功效</span>和蛋白质-配体互动等挑战,借助QC<span style="color: black;">准许</span>对电子进行显式处理的特性,或将得到改善。<span style="color: black;">另外</span>,相比Google的AI模型,<span style="color: black;">必须</span>120多台高端计算机<span style="color: black;">连续</span><span style="color: black;">几周</span>,QC会实现更强大的计算效率。</span><strong style="color: blue;"><span style="color: black;">分子生成和验证</span></strong><span style="color: black;">现有计算机的瓶颈在于<span style="color: black;">次序</span>方式、算力不足,制药<span style="color: black;">机构</span>只能在中小型候选<span style="color: black;">药品</span>上<span style="color: black;">运用</span>CADD。有了足够强大的QC,制药<span style="color: black;">机构</span>能将所有用例扩展到选定的生物制剂,如半合成生物制剂或融合蛋白,并以更高通量进行计算机搜索和验证实验。这个用例将超越蛋白质识别,涵盖几乎<span style="color: black;">全部</span>已知的生物界。</span><strong style="color: blue;"><span style="color: black;">先导化合物优化</span></strong><span style="color: black;">QC<span style="color: black;">能够</span><span style="color: black;">加强</span>吸收、分布和代谢,更准确的器官系统活动和毒性预测以及剂量和溶解度优化等安全问题,这是<span style="color: black;">加强</span><span style="color: black;">开发</span>生产力的三大参数。</span><strong style="color: blue;"><span style="color: black;">数据联动与生成</span></strong><span style="color: black;"><span style="color: black;">经过</span>有效语义管理在数据点之间<span style="color: black;">创立</span><span style="color: black;">恰当</span>的连接,这是<span style="color: black;">药品</span><span style="color: black;">开发</span>的核心技术之一。<span style="color: black;">日前</span>业内正在进行“拓扑数据分析”的<span style="color: black;">科研</span>,旨在识别大型数据集的“漏洞”和“连接”。<span style="color: black;">另外</span>,QC可在<span style="color: black;">全部</span><span style="color: black;">科研</span>过程中“deepfake”缺失的数据点,即<span style="color: black;">运用</span>ML算法生成一种假数据。这在罕见病一类数据稀缺的<span style="color: black;">地区</span>尤其有用,继而<span style="color: black;">经过</span>人工数据集来补足。</span><strong style="color: blue;"><span style="color: black;">临床<span style="color: black;">实验</span></span></strong><span style="color: black;">临床<span style="color: black;">实验</span><span style="color: black;">能够</span><span style="color: black;">经过</span><span style="color: black;">病人</span>识别、分层以及群体<span style="color: black;">药品</span>遗传学模型进行优化。在<span style="color: black;">实验</span>计划和执行中,QC可优化<span style="color: black;">实验</span>地点,<span style="color: black;">加强</span>副<span style="color: black;">功效</span>的因果关系分析,以改善主动安全监测。</span><span style="color: black;"><strong style="color: blue;"><span style="color: black;">03</span></strong></span><span style="color: black;"><strong style="color: blue;">当下的产业化趋势</strong></span><span style="color: black;">量子计算技术日益成熟,其在制药行业的应用趋势如下图:</span><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablzEvW01YHmyPBOSZFPIKic1MOT7c4OibzC14SiajQsibdsD8YAJsGjcz1Qb8lElwIc6ic7KSu4SU4eiacwQ/640?wx_fmt=png&amp;tp=webp&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1" style="width: 50%; margin-bottom: 20px;"><span style="color: black;">2020年-2030年为初步应用期,量子计算将在部分创新药企及制药的个别环节得到应用;2030年之后,<span style="color: black;">经过</span>质量<span style="color: black;">掌控</span>发挥更大价值,制药<span style="color: black;">机构</span>将更<span style="color: black;">稳妥</span>地进入该<span style="color: black;">行业</span>。</span><strong style="color: blue;"><span style="color: black;"><span style="color: black;">那样</span>药企们何时<span style="color: black;">起始</span><span style="color: black;">得到</span>QC的好处?</span></strong><span style="color: black;">这取决于技术起点(当前的数字化水平)及业务重点,即<span style="color: black;">制品</span>组合中小型活性<span style="color: black;">药品</span><span style="color: black;">成份</span>(API) 的数量。</span><span style="color: black;">在CADD<span style="color: black;">行业</span><span style="color: black;">持有</span>强大足迹,并将<span style="color: black;">开发</span>重点放在小分子上的药企将率先利用新兴QC技术。</span><span style="color: black;">接下来的五到十年内,麦肯锡团队预测:药企<span style="color: black;">安排</span>的首批QC<span style="color: black;">工具</span>将依赖于混合<span style="color: black;">办法</span>,即<span style="color: black;">运用</span>经典算法和QC子程序来创造额外价值。<span style="color: black;">例如</span>变分量子本征求解器,或VQE(一种计算API和靶受体)。</span><span style="color: black;"><strong style="color: blue;">04</strong></span><span style="color: black;"><strong style="color: blue;"><span style="color: black;">药企们的行动指南</span></strong></span><span style="color: black;">AI制药<span style="color: black;">公司</span>们<span style="color: black;">已然</span>搭建了良好的技术<span style="color: black;">基本</span>,如CADD、AI、ML等;部分<span style="color: black;">机构</span><span style="color: black;">已然</span>在<span style="color: black;">运用</span>量子化学模拟,<span style="color: black;">因此呢</span>进入门槛很低。</span><span style="color: black;">科学家们<span style="color: black;">亦</span><span style="color: black;">没</span>需改变<span style="color: black;">研发</span><span style="color: black;">药品</span>的方式,只是需<span style="color: black;">运用</span>功能更强大的<span style="color: black;">工具</span>。</span><span style="color: black;"><span style="color: black;">没</span>论是等待观望,或全力以赴,以下的战略方针将有助于<span style="color: black;">公司</span><span style="color: black;">按照</span><span style="color: black;">自己</span><span style="color: black;">状况</span>做出明智决策:</span><strong style="color: blue;"><span style="color: black;"><span style="color: black;">第1</span>,<span style="color: black;">评定</span>机会<span style="color: black;">体积</span>。</span></strong><span style="color: black;">在当前的发展速度下,每家药企都应弄清楚它<span style="color: black;">持有</span>多少<span style="color: black;">揭发</span>率以及其QC机会的<span style="color: black;">体积</span>。</span><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablzEvW01YHmyPBOSZFPIKic1Mxm22tjf3aTicyNiay3oE7tSqEyWbCZcyReBp9LicBkDALh8V1tcYw34qQ/640?wx_fmt=png&amp;tp=webp&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1" style="width: 50%; margin-bottom: 20px;"><span style="color: black;">麦肯锡团队提出了三大问题辅助判断:</span><span style="color: black;">QC会颠覆<span style="color: black;">机构</span>所在的<span style="color: black;">行业</span>并重组竞争格局吗?</span><span style="color: black;"><span style="color: black;">机构</span>的价值链中有<span style="color: black;">表现</span>QC价值的<span style="color: black;">行业</span>吗?将<span style="color: black;">出现</span>在什么时候?</span><span style="color: black;"><span style="color: black;">机构</span><span style="color: black;">能够</span>投入资源来调查QC的机会吗?</span><strong style="color: blue;"><span style="color: black;">第二,<span style="color: black;">创立</span>伙伴关系。</span></strong><span style="color: black;">个别<span style="color: black;">机构</span><span style="color: black;">已然</span><span style="color: black;">起始</span>在量子计算<span style="color: black;">行业</span>展开合作,如QuPharm联盟,由葛兰素史克、武田、辉瑞、默克和艾伯维等<span style="color: black;">构成</span>,成员<span style="color: black;">已然</span><span style="color: black;">一起</span><span style="color: black;">研发</span>了20多个QC在制药行业应用的案例。</span><span style="color: black;">其他跨行业的QC研究联盟,如NEASQC和 QED-C,成员中<span style="color: black;">包含</span>少量制药<span style="color: black;">机构</span>。</span><strong style="color: blue;"><span style="color: black;">第三,提早培养人才。</span></strong><span style="color: black;">数字人才缺口<span style="color: black;">已然</span><span style="color: black;">作为</span>现实,QC可能只会加剧这种缺口。而勃林格殷格翰、安进和罗氏<span style="color: black;">已然</span><span style="color: black;">创立</span>了由药理学<span style="color: black;">专家</span>、<span style="color: black;">理学</span>学家和计算<span style="color: black;">专家</span><span style="color: black;">构成</span>的QC团队。</span><strong style="color: blue;"><span style="color: black;">第四,<span style="color: black;">保证</span>内部协作。</span></strong><span style="color: black;">将内部<span style="color: black;">科研</span>、技术、业务等职能<span style="color: black;">分部</span>的工作<span style="color: black;">掰开</span>,沟通、行动上的跨职能协作将<span style="color: black;">作为</span>充分利用QC的制药<span style="color: black;">机构</span>的新特征。</span><span style="color: black;">量子计算可能是以指数方式更有效地<span style="color: black;">发掘</span><span style="color: black;">药品</span>治疗和治疗<span style="color: black;">办法</span>,以及为制药行业创造数千亿美元价值的<span style="color: black;">重要</span>。</span><strong style="color: blue;"><span style="color: black;">麦肯锡团队预计:到2030年,<span style="color: black;">全世界</span>制药<span style="color: black;">机构</span>在<span style="color: black;">开发</span>方面的QC支出将达到数十亿美元。</span></strong><span style="color: black;"><span style="color: black;">意见</span>药企们自己<span style="color: black;">评定</span>机会,并<span style="color: black;">起始</span>为自己在新的竞争赛道中打下<span style="color: black;">基本</span>。</span><span style="color: black;"><strong style="color: blue;"><span style="color: black;">附录:应用AI+量子技术的部分<span style="color: black;">公司</span></span></strong></span><strong style="color: blue;"><span style="color: black;">1、晶泰科技(XtalPi)</span></strong><span style="color: black;">晶泰科技于2014年创立,是一家基于量子<span style="color: black;">理学</span>学的人工智能<span style="color: black;">药品</span><span style="color: black;">开发</span><span style="color: black;">机构</span>,其使命是<span style="color: black;">经过</span><span style="color: black;">加强</span>速度、规模、新颖性和成功率来彻底改变<span style="color: black;">药品</span><span style="color: black;">发掘</span>和<span style="color: black;">研发</span>。总部<span style="color: black;">位置于</span>波士顿,2015年回到中国开展全面的<span style="color: black;">科研</span>业务。</span><span style="color: black;">其智能数字<span style="color: black;">药品</span><span style="color: black;">发掘</span>和<span style="color: black;">研发</span>平台——ID4,结合了量子力学、人工智能和高性能云计算算法,<span style="color: black;">准许</span>以高精度预测小分子候选<span style="color: black;">药品</span>的<span style="color: black;">理学</span>和化学特性,以及它们的晶体结构。</span><span style="color: black;"><span style="color: black;">日前</span>,晶泰科技累计筹集7.864亿美元,投资<span style="color: black;">公司</span><span style="color: black;">包含</span>红杉中国、腾讯和谷歌,这使其<span style="color: black;">作为</span>市场上资金最充足的计算<span style="color: black;">药品</span><span style="color: black;">发掘</span>初创<span style="color: black;">机构</span>之一。并与<span style="color: black;">包含</span>辉瑞在内的制药<span style="color: black;">机构</span>进行了多项<span style="color: black;">科研</span>合作。</span><strong style="color: blue;"><span style="color: black;">2、Aqemia</span></strong><span style="color: black;">由ÉcoleNormale Supérieure<span style="color: black;">机构</span>孵化,总部<span style="color: black;">位置于</span>法国。其首席执行官兼联合创始人Maximilien Levesque博士8年来<span style="color: black;">始终</span>致力于<span style="color: black;">科研</span>算法,<span style="color: black;">机构</span>结合量子计算和人工智能两大技术来从头设计小分子<span style="color: black;">药品</span>。</span><span style="color: black;"><span style="color: black;">运用</span>量子启发统计力学算法——基于结构的铅状分子设计,可准确预测化合物和治疗靶点之间的亲和力,并且比竞争对手快10,000倍;<span style="color: black;">另外</span>,其AI平台可从亲和力预测器<span style="color: black;">得到</span>反馈,并生成准确性更高的化合物。</span><span style="color: black;">2022年2月,Aqemia宣布与强生合作一项试点<span style="color: black;">科研</span>,利用其量子<span style="color: black;">理学</span>学驱动的<span style="color: black;">药品</span><span style="color: black;">发掘</span>技术,<span style="color: black;">按照</span>Janssen<span style="color: black;">选取</span>基于<span style="color: black;">理学</span>计算的数据集,预测给定靶标的小分子效力。6月,与赛诺菲开展肿瘤学<span style="color: black;">行业</span>的分子设计和<span style="color: black;">药品</span><span style="color: black;">发掘</span>合作,这是继2020年底双方达成合作的最新<span style="color: black;">发展</span>。</span><strong style="color: blue;"><span style="color: black;">3、Hafnium Labs</span></strong><span style="color: black;">Hafnium Labs于2018年在丹麦成立,是一家<span style="color: black;">初期</span>初创<span style="color: black;">机构</span>。<span style="color: black;">科研</span>人员<span style="color: black;">研发</span>了Q-props 和 Epsilon 两个软件包,前者用于高精度模拟纯组分及混合物的<span style="color: black;">理学</span>性质,后者<span style="color: black;">重点</span>是模拟电解质。</span><span style="color: black;">两款软件<span style="color: black;">制品</span>都结合了量子化学、人工智能(AI)和云计算的最新技术,以达到高精度预测。</span><span style="color: black;"><span style="color: black;">经过</span>其基于云的计算能力,该<span style="color: black;">机构</span>可准确预测化学,以加速<span style="color: black;">药品</span><span style="color: black;">发掘</span>、新材料<span style="color: black;">研发</span>等<span style="color: black;">行业</span>。<span style="color: black;">另外</span>,它还<span style="color: black;">拥有</span>按<span style="color: black;">运用</span>付费的<span style="color: black;">商场</span>模式,与基于许可证的模式相比,该<span style="color: black;">机构</span><span style="color: black;">叫作</span>这种模式更实惠。</span><span style="color: black;">到<span style="color: black;">日前</span>为止,Hafnium Labs<span style="color: black;">已然</span><span style="color: black;">经过</span>丹麦创新基金,IBM和Climate-KIC加速计划(EIT)的赠款筹集了总计180万美元。</span><strong style="color: blue;"><span style="color: black;">4、Kuano</span></strong><span style="color: black;">成立于2020年初,是一家总部<span style="color: black;">位置于</span>英国的初创<span style="color: black;">机构</span>,<span style="color: black;">日前</span>正在<span style="color: black;">研发</span>用于设计酶的新型AI和量子<span style="color: black;">处理</span><span style="color: black;">方法</span>,以<span style="color: black;">处理</span>特异性、效力和耐药性等<span style="color: black;">重要</span>问题。<span style="color: black;">日前</span>已筹集了140万美元的种子轮资金。</span><span style="color: black;">Kuano的<span style="color: black;">科研</span>平台利用<span style="color: black;">目的</span>酶或催化位点的结构数据,将量子模拟与量子启发的人工智能和化学相结合。</span><span style="color: black;">在表观遗传学、蛋白质降解、免疫代谢及传<span style="color: black;">患病</span>等方面<span style="color: black;">持有</span>内部项目,<span style="color: black;">同期</span>与合作伙伴<span style="color: black;">研发</span>临床和<span style="color: black;">商场</span>验证酶靶标的下一代<span style="color: black;">控制</span>剂。</span><strong style="color: blue;"><span style="color: black;">5、Menten AI</span></strong><span style="color: black;">一家成立于2018年的加拿大初创<span style="color: black;">机构</span>,致力于<span style="color: black;">研发</span>由<span style="color: black;">设备</span>学习和量子计算驱动的蛋白质设计软件平台。该<span style="color: black;">机构</span><span style="color: black;">运用</span>量子优化的专有算法,<span style="color: black;">由于</span>其不仅能<span style="color: black;">加强</span><span style="color: black;">药品</span><span style="color: black;">发掘</span>的准确性,<span style="color: black;">同期</span>降低成本和<span style="color: black;">研发</span>时间。</span><span style="color: black;">MentenAI为<span style="color: black;">日前</span>的量子计算机创建了蛋白质设计算法,并<span style="color: black;">作为</span><span style="color: black;">第1</span>家应用量子计算机来设计蛋白质分子的团队。</span><span style="color: black;">该<span style="color: black;">机构</span>声<span style="color: black;">叫作</span>,<span style="color: black;">她们</span><span style="color: black;">能够</span>在不到六个月的时间内完成一个设计周期,从靶标<span style="color: black;">选取</span>到<span style="color: black;">身体</span>功效。<span style="color: black;">重点</span><span style="color: black;">开发</span>管道为肽疗法,用于<span style="color: black;">拥有</span>高度未满足医疗需求的适应症。</span><span style="color: black;">截止<span style="color: black;">日前</span>,已筹集近400万美元。并与D-Wave超级计算机、IBM-Q<span style="color: black;">创立</span>了合作关系,<span style="color: black;">近期</span>宣布与Xanadu合作。</span><span style="color: black;"><span style="color: black;">关联</span>阅读:</span><a style="color: black;"><span style="color: black;"><span style="color: black;">刚才</span>融资2亿美元的制药<span style="color: black;">机构</span>宣布收购量子计算初创<span style="color: black;">公司</span></span></a><a style="color: black;"><span style="color: black;">采用量子技术的AI制药<span style="color: black;">机构</span>融资4亿美元</span></a><a style="color: black;"><span style="color: black;">三位MIT量子<span style="color: black;">理学</span>博士后的跨界制药之旅</span></a><a style="color: black;"><span style="color: black;">在实现<span style="color: black;">全世界</span>首个量子化学模拟后,谷歌正式进入</span></a>制药行业<a style="color: black;"><span style="color: black;"><span style="color: black;">全世界</span>制药行业量子计算创业<span style="color: black;">机构</span>盘点</span></a><span style="color: black;">#</span><a style="color: black;"><span style="color: black;">光子盒视频号开通啦!你要的,这</span><span style="color: black;">里</span><span style="color: black;">全都</span><span style="color: black;">有</span></a><span style="color: black;">#</span><span style="color: black;">每周一到周五,<span style="color: black;">咱们</span>都将与光子盒的新老<span style="color: black;">伴侣</span>相聚在<span style="color: black;">微X</span>视频号,不见不散</span><span style="color: black;">!</span><span style="color: black;"><strong style="color: blue;"><span style="color: black;">你可能会<span style="color: black;">错失</span>:</span></strong></span><a style="color: black;"><span style="color: black;"><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablzbrQaQzjpjTATLYvbFk6j1r0yOYV0n3CIoWVYdlrg5WMSalibnXCaAibgiax6Me9SMZkYjybdPrFvgA/640?wx_fmt=png&amp;tp=webp&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1" style="width: 50%; margin-bottom: 20px;"></span></a><a style="color: black;"><span style="color: black;"><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablzEvW01YHmyPBOSZFPIKic1Mhc2cGKeEZG6jtoHO1xhyYcTtcibGqsv7rdK60B5V7BDtmTlZHRxicticw/640?wx_fmt=png&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1&amp;tp=webp" style="width: 50%; margin-bottom: 20px;"></span></a><img src="https://mmbiz.qpic.cn/sz_mmbiz_jpg/Z6jSflhablwRicCtyP94wRbcBW2kzpyBZm7ZZW1DpMnEs64uxFLficwOFXDTabAzj1Sp0wu5ohWeAWaNPn4frialQ/640?wx_fmt=jpeg&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1&amp;tp=webp" style="width: 50%; margin-bottom: 20px;"><strong style="color: blue;"><img src="https://mmbiz.qpic.cn/sz_mmbiz_png/Z6jSflhablwHCFjyuouPs0eNcsU1UsngxknpzEcrajm8pD15iamICEXcVVicOI8I8T4KCqISAiaZbxOC9b7nnpLww/640?wx_fmt=png&amp;wxfrom=5&amp;wx_lazy=1&amp;wx_co=1&amp;tp=webp" style="width: 50%; margin-bottom: 20px;"></strong>




4zhvml8 发表于 2024-10-5 12:34:41

对于这个问题,我有不同的看法...

nykek5i 发表于 2024-10-17 03:11:42

外链发布论坛学习网络优化SEO。

nqkk58 发表于 2024-11-3 06:11:48

期待与你深入交流,共探知识的无穷魅力。

7wu1wm0 发表于 2024-11-9 15:57:30

我们有着相似的经历,你的感受我深有体会。
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