Manager, Evidence Generation Study Design & Execution Lead

Takeda Innovation Solutions Mexico S.A de C.V

🇮🇳 India
Hybrid
Manager or above
17 hours ago

landscaping
AI

17 hours ago

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Job Description

About the Role:

Support study concept development, including data and evidence source landscaping, study synopsis drafting support, protocol drafting support, review coordination, scenario planning, comment collation, version tracking, and final review package preparation.

Provide structured drafting, documentation, and coordination support to enable Global Evidence Generation to define evidence questions, study concepts, scientific design, methodology strategy, source selection, and final sign-offs.

How You Will Contribute

Evidence Source Landscaping

Conduct source landscaping across real-world data, registries, claims, electronic health records, clinical trials, literature, primary data collection, and other available evidence sources.
Summarize source coverage, strengths, limitations, access constraints, quality considerations, and selection tradeoffs.
Prepare source-landscape outputs and store source summaries and decision rationale in the appropriate repository.
Synopsis and Protocol Support
Draft synopsis shells, first-pass synopsis content, simpler or standardized protocol sections, and supporting materials using approved templates and approved AI support where applicable.
Review and manually refine AI-supported or first-pass content for clarity, completeness, formatting, and alignment with study intent.
Update synopsis and protocol versions, track changes, collate comments, and prepare final review packages.
Route final approved materials and maintain review history, comments, decisions, and supporting evidence.
Cross-Functional Review Coordination
Gather input from required stakeholders through appropriate forums or systems in accordance with standard operating procedures.
Collate open questions, conflicting inputs, decision points, and action items for Global Evidence Generation review.
Escalate scientific, strategic, design, methodology, source-selection, or operational issues to Global Evidence Generation owners.
Support standardization of study templates, source-landscaping outputs, review trackers, and handoff materials.
Digital, Automation, and AI-Enabled Ways of Working
Use approved AI-supported drafting tools to develop first-pass study content and supporting materials where appropriate.
Apply human review to AI-supported outputs to confirm clarity, completeness, scientific alignment, traceability, privacy, quality, and compliance.
Use approved digital tools, evidence repositories, and study systems to maintain source summaries, version history, review comments, decisions, and final materials.
Identify repeatable study-design support activities that may benefit from standardization or responsible automation.

Skills and Qualifications

·More than 3 years of related work experience and more than 2 years of experience in the biopharmaceutical industry.
Experience in evidence generation, clinical or study operations, real-world evidence or HEOR operations, study design support, protocol coordination, medical writing operations, or scientific project coordination is preferred.
Experience coordinating cross-functional review, maintaining version-controlled study materials, and preparing review packages is preferred.
Technical and Functional Skills
Working knowledge of evidence generation study design, protocol and synopsis workflows, data-source landscaping, and cross-functional review coordination.
Ability to summarize evidence-source options, limitations, access constraints, quality considerations, and selection tradeoffs.
Familiarity with study synopsis and protocol templates, version control, comment collation, and review-package preparation.
Strong scientific writing, documentation, organization, and cross-functional coordination skills.
Familiarity with approved AI-supported drafting tools, evidence repositories, real-world data sources, and study systems is preferred.
Ability to recognize and escalate scientific, strategic, design, methodology, source-selection, and operational issues to appropriate accountable owners.
Ability to manage multiple concurrent study-development workstreams while maintaining accurate, complete, and traceable documentation.

Education

· A degree in a scientific, medical, life sciences, pharmacy, public health, epidemiology, medical writing, health economics, or related discipline is required.

Benefits

It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are:

Competitive Salary + Performance Annual Bonus

Flexible work environment, including hybrid working
Comprehensive Healthcare Insurance Plans for self, spouse, and children
Group Term Life Insurance and Group Accident Insurance programs
Health & Wellness programs including annual health screening, weekly health sessions for employees.
Employee Assistance Program
5 days of leave every year for Voluntary Service in addition to Humanitarian Leaves
Broad Variety of learning platforms
Diversity, Equity, and Inclusion Programs
No Meeting Days
Reimbursements – Home Internet & Mobile Phone
Employee Referral Program
Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 days)

About ICC in Takeda

Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day.
As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.

Time Type

Full time

Manager, Evidence Generation Study Design & Execution Lead · Takeda Innovation Solutions Mexico S.A de C.V

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