Biotech Patent Landscape Analyzer
Analyze biotech and pharmaceutical patent landscapes to identify opportunities, assess competition, and guide R&D strategy.
When to Use
- - Use this skill when the task needs Use when analyzing biotech patent landscapes, identifying white spaces in pharmaceutical IP, tracking competitor patents, or assessing freedom to operate for drug development. Provides comprehensive patent analysis and strategic insights for life sciences innovation.
- Use this skill for evidence insight tasks that require explicit assumptions, bounded scope, and a reproducible output format.
- Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.
Key Features
- - Scope-focused workflow aligned to: Use when analyzing biotech patent landscapes, identifying white spaces in pharmaceutical IP, tracking competitor patents, or assessing freedom to operate for drug development. Provides comprehensive patent analysis and strategic insights for life sciences innovation.
- Packaged executable path(s):
scripts/main.py. - Reference material available in
references/ for task-specific guidance. - Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
- -
Python: 3.10+. Repository baseline for current packaged skills. - INLINECODE4 :
not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.
Example Usage
CODEBLOCK0
Example run plan:
- 1. Confirm the user input, output path, and any required config values.
- Edit the in-file
CONFIG block or documented parameters if the script uses fixed settings. - Run
python scripts/main.py with the validated inputs. - Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See ## Workflow above for related details.
- - Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
scripts/main.py. - Reference guidance:
references/ contains supporting rules, prompts, or checklists. - Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Quick Check
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
CODEBLOCK1
Audit-Ready Commands
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
CODEBLOCK2
Workflow
- 1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
- Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
- Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
- Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
- If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.
Quick Start
CODEBLOCK3
Core Capabilities
1. Patent Search & Analysis
CODEBLOCK4
Search Strategies:
- - Keyword-based: Technical terms + synonyms
- Classification-based: IPC/CPC codes
- Citation-based: Forward/backward citations
- Assignee-based: Company portfolios
2. White Space Analysis
CODEBLOCK5
White Space Opportunities:
- - Underserved disease indications
- Novel combination therapies
- Alternative delivery mechanisms
- Geographical gaps (emerging markets)
3. Competitor Intelligence
CODEBLOCK6
Competitor Metrics:
| Metric | Description |
|---|
| Portfolio size | Total active patents |
| Filing velocity |
Recent filing trends |
| Geographic coverage | Jurisdiction strategy |
| Technology focus | Core vs. peripheral areas |
| Partnership patterns | Collaboration trends |
4. Freedom to Operate (FTO) Assessment
CODEBLOCK7
FTO Analysis Steps:
- 1. Identify relevant patent claims
- Map claims to product features
- Assess validity of blocking patents
- Design around options
- Licensing recommendations
CLI Usage
CODEBLOCK8
Data Sources
- - USPTO (United States)
- EPO (Europe)
- WIPO (Global)
- JPO (Japan)
- CNIPA (China)
References
- -
references/ipc-classifications.md - IPC/CPC codes for biotech - INLINECODE12 - Advanced search techniques
- INLINECODE13 - Sample reports
Skill ID: 204 |
Version: 1.0 |
License: MIT
Output Requirements
Every final response should make these items explicit when they are relevant:
- - Objective or requested deliverable
- Inputs used and assumptions introduced
- Workflow or decision path
- Core result, recommendation, or artifact
- Constraints, risks, caveats, or validation needs
- Unresolved items and next-step checks
Error Handling
- - If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback. - Do not fabricate files, citations, data, search results, or execution outcomes.
Input Validation
This skill accepts requests that match the documented purpose of patent-landscape and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
INLINECODE16 only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
References
Response Template
Use the following fixed structure for non-trivial requests:
- 1. Objective
- Inputs Received
- Assumptions
- Workflow
- Deliverable
- Risks and Limits
- Next Checks
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.
生物技术专利景观分析器
分析生物技术和制药专利景观,以识别机会、评估竞争并指导研发战略。
使用时机
- - 当任务需要分析生物技术专利景观、识别制药知识产权中的空白领域、追踪竞争对手专利或评估药物开发的自由实施权时,使用此技能。提供全面的专利分析和生命科学创新的战略洞察。
- 用于需要明确假设、限定范围和可重复输出格式的证据洞察任务。
- 当需要为缺失输入、执行错误或部分证据提供有文档记录的备用路径时,使用此技能。
主要特性
- - 聚焦范围的工作流程,与以下内容对齐:用于分析生物技术专利景观、识别制药知识产权中的空白领域、追踪竞争对手专利或评估药物开发的自由实施权。提供全面的专利分析和生命科学创新的战略洞察。
- 打包的可执行路径:scripts/main.py。
- 参考资料位于 references/ 目录,提供任务特定指导。
- 结构化执行路径,旨在保持输出一致且可审查。
依赖项
- - Python:3.10+。当前打包技能的仓库基线。
- 第三方包:本技能包中未明确固定版本。如果此技能需要更严格的环境控制,请添加固定版本。
使用示例
bash
cd 20260318/scientific-skills/Evidence Insight/patent-landscape
python -m py_compile scripts/main.py
python scripts/main.py --help
示例运行计划:
- 1. 确认用户输入、输出路径以及任何必需的配置值。
- 如果脚本使用固定设置,编辑文件内的 CONFIG 块或文档化参数。
- 使用验证后的输入运行 python scripts/main.py。
- 审查生成的输出,并返回最终成果,同时注明任何假设。
实现细节
参见上述 ## 工作流程 了解相关细节。
- - 执行模型:验证请求,选择打包的工作流程,并生成限定的可交付成果。
- 输入控制:在运行任何脚本前,确认源文件、范围限制、输出格式和验收标准。
- 主要实现界面:scripts/main.py。
- 参考指南:references/ 包含支持规则、提示或检查清单。
- 需首先明确的参数:输入路径、输出路径、范围过滤器、阈值以及任何领域特定约束。
- 输出纪律:保持结果可重复,明确识别假设,避免未记录的副作用。
快速检查
在深入执行前,使用此命令验证打包脚本入口点是否可解析。
bash
python -m py_compile scripts/main.py
审计就绪命令
使用这些具体命令进行验证。它们特意设计为自包含,避免使用占位符路径。
bash
python -m py_compile scripts/main.py
python scripts/main.py --help
工作流程
- 1. 在进行详细工作前,确认用户目标、所需输入和不可协商的约束条件。
- 验证请求是否与文档化范围匹配,如果任务需要不支持的假设,则尽早停止。
- 仅使用实际可用的输入,使用打包脚本路径或文档化的推理路径。
- 返回结构化结果,将假设、可交付成果、风险和未解决事项分开。
- 如果执行失败或输入不完整,切换到备用路径,并准确说明阻止完全完成的原因。
快速入门
python
from scripts.patent_landscape import PatentLandscapeAnalyzer
analyzer = PatentLandscapeAnalyzer()
分析治疗领域
landscape = analyzer.analyze(
therapeutic_area=CAR-T细胞疗法,
date_range=2020-2024,
assignees=[诺华, 凯特制药, 朱诺治疗]
)
核心能力
1. 专利检索与分析
python
results = analyzer.search_patents(
keywords=[CRISPR, 基因编辑, 治疗],
classification=C12N15/113, # IPC分类
jurisdictions=[US, EP, WO]
)
检索策略:
- - 基于关键词:技术术语 + 同义词
- 基于分类:IPC/CPC代码
- 基于引用:前向/后向引用
- 基于申请人:公司专利组合
2. 空白领域分析
python
opportunities = analyzer.identifywhitespaces(
technology=抗体药物偶联物,
target_diseases=[乳腺癌, 肺癌],
existing_claims=landscape
)
空白领域机会:
- - 服务不足的疾病适应症
- 新型联合疗法
- 替代递送机制
- 地理空白(新兴市场)
3. 竞争对手情报
python
competitors = analyzer.analyze_competitors(
companies=[辉瑞, 莫德纳, BioNTech],
focus_area=mRNA疫苗
)
竞争对手指标:
近期申请趋势 |
| 地理覆盖范围 | 管辖区域策略 |
| 技术重点 | 核心与外围领域 |
| 合作模式 | 协作趋势 |
4. 自由实施权(FTO)评估
python
fto = analyzer.assess_fto(
product_concept=靶向PD-1和CTLA-4的双特异性抗体,
jurisdictions=[US, EU, Japan]
)
FTO分析步骤:
- 1. 识别相关专利权利要求
- 将权利要求映射到产品特征
- 评估阻碍专利的有效性
- 规避设计方案
- 许可建议
CLI使用
text
生成专利景观报告
python scripts/patent_landscape.py \
--query 免疫肿瘤检查点抑制剂 \
--output landscape_report.pdf \
--format comprehensive
快速FTO检查
python scripts/patent_landscape.py \
--fto product_description.txt \
--jurisdictions US EP JP
数据来源
- - USPTO(美国)
- EPO(欧洲)
- WIPO(全球)
- JPO(日本)
- CNIPA(中国)
参考资料
- - references/ipc-classifications.md - 生物技术IPC/CPC代码
- references/patent-search-strategies.md - 高级检索技术
- examples/landscape-reports/ - 示例报告
技能ID:204 |
版本:1.0 |
许可证:MIT
输出要求
每个最终响应应在相关时明确以下内容:
- - 目标或请求的可交付成果
- 使用的输入和引入的假设
- 工作流程或决策路径
- 核心结果、建议或成果
- 约束条件、风险、注意事项或验证需求
- 未解决事项和后续检查
错误处理
- - 如果缺少必需输入,准确说明哪些字段缺失,并仅请求最少量的额外信息。
- 如果任务超出文档化范围,停止执行,而不是猜测或悄悄扩大任务范围。
- 如果 scripts/main.py 失败,报告失败点,总结仍可安全完成的内容,并提供手动备用方案。
- 不要编造文件、引用、数据、搜索结果或执行结果。
输入验证
此技能接受与 patent-landscape 文档化目的匹配且包含足够上下文以安全完成工作流程的请求。
当请求超出范围、缺少关键输入或需要不支持的假设时,不要继续工作流程。而是响应:
patent-landscape 仅处理其文档化的工作流程。请提供缺失的必需输入或切换到更合适的技能。
参考资料
响应模板
对于非平凡请求,使用以下固定结构:
- 1. 目标
- 收到的输入
- 假设
- 工作流程
- 可交付成果
- 风险与限制
- 后续检查
如果请求简单,可以压缩结构,但在影响正确性时仍需明确说明假设和限制。