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嘉峪檢測網 2025-04-28 19:49
In the highly regulated world of pharmaceuticals and life sciences, risk isn’t just a numerical score — it’s a story of what might happen. Regulatory frameworks like ICH Q9 and ISO 31000 anchor our approaches to quality risk management (QRM), but even with all this guidance, a silent disruptor often creeps in: subjectivity.
在高度監管的制藥和生命科學領域，風險不僅僅是一個數字分數——它是一個可能發生的故事。如ICH Q9和ISO 31000這樣的監管框架為我們的質量風險管理（QRM）方法奠定了基礎，但即使有了所有這些指導，一個無聲的破壞者經常潛入：主觀性。
Subjectivity is both a threat and an opportunity. If unchecked, it clouds judgement, introduces bias, and can lead to decisions that fail to prevent harm to patients. But when understood and managed properly, subjectivity becomes a source of creativity, revealing hidden hazards and unlocking more effective risk controls. The delicate balance of subjectivity management has been acknowledged in the recent FDA and ICH Q9 R1 updates, which bring subjectivity into the spotlight as a factor that can undermine the effectiveness of QRM if not properly addressed.
主觀性既是威脅，也是機遇。如果不加以控制，它會使判斷變得模糊，引入偏見，并可能導致無法防止對患者造成傷害的決定。但是，如果理解和管理得當，主觀性就會成為創造力的源泉，揭示隱藏的危害并解鎖更有效的風險控制。主觀性管理的微妙平衡在最近的 FDA 和 ICH Q9 R1 更新中得到了認可，這些更新將主觀性作為一項因素成為人們關注的焦點，如果處理不當，可能會破壞 QRM 的有效性。
How Subjectivity Can Lead To Catastrophe
主觀性如何導致災難
In life sciences, risk management is about anticipating and preventing harm to the patient. Here are some challenges we often face:
在生命科學中，風險管理涉及預測和預防對患者的傷害。以下是我們經常面臨的一些挑戰：
Risk is abstract. We are trying to imagine what might happen in the future.
風險是抽象的。我們要試圖想象未來會發生什么。
Subjectivity thrives in the absence of hard data, especially in novel or complex systems.
主觀性在缺乏硬數據的情況下蓬勃發展，特別是在新穎或復雜的系統中。
Group collaboration, while necessary, often amplifies rather than mitigates this subjectivity.
團隊合作是必要的，但有時會放大而不是減輕這種主觀性。
Ultimately, a failure to imagine what can go wrong may lead to a catastrophe when something does go wrong. And imagination is a subjective process by nature.
最終，無法想象當事情出了問題時，什么可能會出錯，什么會導致災難。想象本質上是一個主觀的過程。
Some Common Subjectivity Pitfalls During Risk Assessment
風險評估過程中一些常見的主觀性陷阱
In theory, risk assessments should be rational and evidence-based but in reality, they are often subjective and shaped by our biases. Let’s look at some examples of how these cognitive bias traps show up in risk assessment:
理論上，風險評估應該是理性的、基于證據的，但實際上，它們往往是主觀的，受到偏見的影響。讓我們來看一些例子，看看這些認知偏見的陷阱是如何在風險評估中出現的：
Anchoring bias
錨定偏見（一種認知偏差，指在做決策時過度依賴或受到先前獲得的信息（錨定點）的影響，而忽視其他相關信息。）
“We’ve always done it this way.”
“我們一直都是這么做的。”
Imagine a risk assessment session for a new lab information management system (LIMS). A participant immediately brings the supplier qualification assessment to the table, and this becomes the focal point. Even if the need for customization is actually the more pressing risk to discuss, the discussion never drifts far from that first anchor. As a result, mitigations are focused on the frequency of supplier requalification instead of addressing deeper issues like system configuration or customization errors.
想象一個新的實驗室信息管理系統（LIMS）的風險評估會議。參與者立即將供應商資質評估帶到桌面上，這成為焦點。即使定制化需求實際上是需要討論的更緊迫的風險，討論也不會偏離第一個錨點。因此，風險控制措施集中在供應商再確認的頻率上，而不是解決更深層次的問題，如系統配置或定制錯誤。
Groupthink
從眾思維
“Nobody wanted to challenge the plan.”
“沒有人想去挑戰這個計劃。”
A team is evaluating a cloud-based eQMS implementation. Everyone agrees it's low risk because the vendor is reputable in other industries. One junior IT analyst hesitates but stays quiet — the group seems united. Later, the company experiences a regulatory citation due to inadequate audit trail capabilities, which the analyst had noticed but didn’t flag. The desire to avoid conflict trumped risk identification.
一個團隊正在評估基于云的QMS系統的實施。每個人都認為這是低風險的，因為供應商在其他行業有信譽。一位初級IT分析師猶豫了一下，但然后保持沉默——整個團隊似乎很團結。后來，由于審計追蹤能力缺陷，該公司受到了監管部門的處罰，那個分析師注意到了這一點，但沒有指出。避免沖突的愿望壓倒了風險識別。
Loudest voice bias
最大聲偏差
“Mandy said it was fine, so we moved on.”
“QA主管說沒關系，所以我們就繼續了。”
During a supplier qualification session, Mandy — the head of site quality — dominates. She focuses on GMP documentation compliance, pushing aside logistics risks raised by a new supply chain team member. The result? Supplier delivery failures that impact production timelines — risks that were overlooked because one voice overpowered the rest.
在一次供應商確認會議上，現場質量主管占了主導地位。她專注于GMP文件合規性，而不顧新供應鏈團隊成員帶來的物流風險。結果呢? 該供應商交貨失敗影響了生產進度——由于一種聲音壓倒了其他聲音從而風險被忽視。
Confirmation bias
證真偏差（證真偏差是一種認知傾向，指人們在信息處理過程中更傾向于關注、解釋和記憶與自身原有觀點一致的信息，而忽視或排斥相悖信息。）
“We found what we were looking for.”
“我看到了我想要的東西。”
A team assesses a legacy system and starts with the assumption that it’s still compliant. They selectively reference older validation reports and skip over emerging vulnerabilities like obsolete encryption protocols. The risk assessment validates their starting belief rather than challenging it. Meanwhile, new vulnerabilities remain unaddressed.
一個團隊評估一個遺留系統，并首先假設它仍然合規。它們有選擇地引用較舊的驗證報告，而跳過新出現的漏洞，例如過時的加密協議。風險評估驗證了他們的初始信念，而不是挑戰它。與此同時，新的漏洞仍未得到解決。
Conjunction fallacy
連詞謬誤（是指人們在判斷事件發生概率時，錯誤地認為兩個事件同時發生的概率大于其中任何一個事件單獨發生的概率）
“It’ll only fail if A, B, and C happen, so it's low risk.”
“只有當 A、B 和 C 同時發生時才會失敗，所以風險很低。”
During a data migration project, the team assumes that system failure would require a cascade: the new system crashing, backups failing, and the restore process being misconfigured. They rate the risk as negligible. But in reality, even one of these failure points would severely disrupt operations. The illusion of complexity makes the risk seem less likely than it is.
在數據遷移項目期間，團隊假設系統故障需要一個級聯：新系統崩潰、備份失敗以及還原過程配置錯誤。他們將風險評為可以忽略不計。但實際上，即使是這些故障中的一個也會嚴重中斷運營。復雜性的錯覺使風險看起來比實際可能性要小。
Sunk-cost fallacy
沉沒成本謬誤（在決策過程中，由于考慮到之前已經投入且無法收回的成本（即沉沒成本），而繼續堅持某一決策或行動，即使這一決策或行動在邏輯上或經濟上已不再合理。簡單來說，就是由于“不甘心”已經付出的努力或金錢，而繼續投入更多資源，即便這些投入可能帶來更大的損失。）
“We’ve already invested so much — let’s keep going.”
“我們已經投入了大量資金——我們要繼續前進。”
Biases are everyday barriers to effective decision-making, and they usually operate silently. When these biases go unchecked, risk assessments can fail to uncover the real hazards that could compromise product quality or patient safety. Without structure and awareness, teams don’t realize they’ve been swayed by bias until something goes wrong.
偏見是有效決策的日常障礙，它們通常悄無聲息。如果這些偏見得不到約束，風險評估可能無法發現可能危及產品質量或患者安全的真正危害。如果沒有組織和意識，團隊不會意識到他們已經被偏見所左右，直到出現問題。
Promoting Creative Hazard Identification
促進創造性的危害識別
The revised ICH Q9 R1 highlights that organizations are vulnerable to human bias. But instead of eliminating subjectivity, the opportunity lies in harnessing creativity by using methodological collaboration. We use “working together alone,” a structured approach built around deliberate collaboration cycles.
ICH Q9 R1 強調組織容易受到人為偏見的影響。但是，與其消除主觀性，不如通過使用方法合作來利用創造力。我們使用“獨立工作”，這是一種圍繞深思熟慮的協作周期構建的結構化方法。
Diverge – Individuals think independently to generate a wide range of hazards.
發散 – 個人獨立思考以廣泛地識別危害。
Converge – The team brings those ideas together to align and make sense of them.
聚合 – 團隊將這些思考聚集在一起，以協調和理解它們。
Decide – The group prioritizes and selects which hazards to carry forward for full risk assessment.
決定 – 團隊確定優先級并選擇要推進以進行全面風險評估的危害。
1. Diverge – Think Independently
發散 – 獨立思考
Each team member begins by identifying potential hazards alone, drawing from their own experience. Without influence from colleagues, everyone is encouraged to tap into their own domain expertise, surface concerns others might not see, and consider risks without fear of being wrong or dismissed.
每個團隊成員首先從自己的經驗中單獨識別潛在的危害。在沒有同事影響的情況下，我們鼓勵每個人利用自己的領域專業知識，提出其他人可能看不到的問題，并考慮風險，而不必擔心出錯或被忽視。
This prevents anchoring, groupthink, or the dominance of senior voices. A QA lead might identify risks related to audit trail integrity in violation of 21 CFR Part 11, while an IT specialist might flag risks around privileged access that go beyond GAMP5 category expectations. Everyone contributes equally, regardless of role or seniority.
這可以防止錨定、從眾思維或最大聲偏差的主導地位。QA 主管可能會識別出違反GMP的審計追蹤完整性相關風險，而 IT 專家可能會識別出超 GAMP5 類別預期的特權訪問風險。無論角色或資歷如何，每個人都有平等的貢獻。
2. Converge – Align And Analyze As A Team
聚合 – 作為一個團隊進行協調和分析
The group reconvenes to share, group, and clarify their hazards. Common themes emerge, gaps are revealed, and insights compound. This step creates shared understanding while preserving the diversity of thought generated during divergence. The group collectively decides which hazards are most relevant for further analysis.
團隊再次召開會議，分享、分組和澄清所識別的危害。共同的主題出現，差距被揭示，洞察力不斷復雜。這一步創造了共同的理解，同時保留了發散過程中產生的思維多樣性。團隊共同決定哪些危害與進一步分析最相關。
3. Decide – Prioritize And Move Forward
決策 – 確定優先級并向前邁進
Finally, the team selects which hazards to assess further — based on potential impact, relevance, and urgency. The decision is made through structured facilitation, sometimes using techniques like dot voting or assigning a decider, ensuring bias doesn’t derail consensus.
最后，團隊根據潛在影響、相關性和緊迫性選擇要進一步評估的危害。決策是通過結構化的促進做出的，有時使用點投票或分配決策者等技術，確保偏見不會破壞共識。
This cycle helps teams imagine what could go wrong before it does go wrong, while reducing the noise and bias that can dominate traditional group discussions.
這個流程有助于團隊在問題出現之前想象哪里可能出錯，同時減少可能主導團隊討論的噪音和偏見。
來源：Internet
