出海雷达

Associate Director, Clinical Pharmacology and Pharmacometrics

其他未标注地域
公司Dianthus Therapeutics
薪资未公开
工作地点Worldwide
地域资格未标注地域
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

我们正在为患有严重自身免疫疾病的患者开发最好的类型治疗方法。我们的抗体,classprubart (DNTH103),是专门设计的,具有延长半衰期,提高功率和高选择性,仅用于活性 C1补充蛋白质,推动了疾病病理,使得自行注射更少频繁且更方便。我们的第二个临床候选人,DNTH212是第一种和潜在最好的类型的双功能抑制剂,该药物针对了临床验证和补充性疾病修改机制,Typ 1 IFN 抑制和 B 细胞调节,从而使得临床结果得到改善和患者友好方便的自行注射。了解更多信息,请访问 www.dianthustx.com 并关注我们在 LinkedIn 上。关于角色的副主任临床药理学与制药计量学将担任公司自身免疫/炎症和神经肌肉疾病投资组合支持的主要定量的科学领导者。这个人将设计,执行和解释量化系统药理学 (QSP),人口制药基因组 (PopPK) 和暴露反应分析 (E-R) 以提供人类第一次剂量选择 (FIH),第二阶段剂量选择/合理性以及生命周期配方/设备桥梁策略的信息。该角色需要深入实践模型专业知识 (MATLAB, NONMEM, R) 结合能力转换复杂数量的输出成清晰,可决策的建议用于跨功能团队和监管提交。这是一个独特的机会,你作为一个由持续创新和非常高科学完整驱动的团队的一部分有机会积极影响生命。我们正在建立一个以我们的核心原则为中心的团队,目的是提高患者生活的关怀。我们在建设个人文化,以我们的核心原理为中心的运作,目标是提高患者?? 生活的关怀,我们对你开放的工作远程。· 开发和应用适合用途的 QSP 模型 (MATLAB 及相关 MATLAB 模块,例如 SimBiology)来描述目标参与/覆盖,RO,PK/PD 关系以及与疾病有关的生物在自身免疫和炎症计划中。·进行竞争性景观分析和基准分析,集成公共信息。

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About Us
We are developing potentially best in class therapies for patients living with severe autoimmune diseases. Our lead antibody, claseprubart (DNTH103), is purposefully engineered with extended half-life, improved potency, and high selectivity for only the active C1s complement protein that drives disease pathology – enabling less frequent and more convenient self-administered subcutaneous injections. Our second clinical candidate, DNTH212 is a first and potentially best in class, bifunctional inhibitor that targets clinically validated and complementary disease modifying mechanisms, Type 1 IFN suppression and B cell modulation – enabling potential for improved clinical outcomes and patient friendly convenient, self-administered subcutaneous injections. To learn more, please visit www.dianthustx.com and follow us on LinkedIn.
About the Role
The Associate Director, Clinical Pharmacology & Pharmacometrics will serve as a key quantitative sciences leader supporting the company's autoimmune/inflammation and neuromuscular disease portfolios. This individual will design, execute, and interpret quantitative systems pharmacology (QSP), population pharmacokinetic (PopPK), and exposure-response (E-R) analyses to inform first-in-human (FIH) dose selection, Phase 2 dose selection/rationale, and lifecycle formulation/device bridging strategies. The role requires deep hands-on modeling expertise (MATLAB, NONMEM, R) combined with the ability to translate complex quantitative outputs into clear, decision-enabling recommendations for cross-functional teams and regulatory submissions.
This is a unique opportunity where you have a chance to positively impact lives as part of the team driven by continuous innovation with very high scientific integrity. We are building a team who hold our core principles at the center of our operations, with the goal to elevate the care of our patients’ lives.
We are building a culture of individuals who hold our core principles at the center of our operations, with the goal to elevate the care of our patients’ lives. We are open to you working remotely.
Key Responsibilities
QSP Modeling & First-in-Human Dose Selection

  • Develop and apply fit-for-purpose QSP models (MATLAB and associated MATLAB modules, e.g., SimBiology) to characterize target engagement/coverage, RO, PK/PD relationships, and disease-relevant biology in autoimmunity and inflammation programs.
  • Conduct competitive landscape and benchmarking analyses, integrating publicly available competitor PK/PD/clinical data into modeling frameworks to contextualize internal program positioning.
  • Integrate nonclinical (in vitro/in vivo/NHP PK/PD) data with competitor-derived and mechanistic assumptions to simulate human PK/PD and support translational dose projections.
  • Lead quantitative dose-selection strategy for first-in-human studies, including starting dose justification, dose-escalation scheme simulation, and safety margin assessment.
  • Use R for exploratory data analysis, visualization, and model diagnostics supporting QSP deliverables.

Population PK/PD and Exposure-Response Analysis

  • Build, qualify, and apply population pharmacokinetic (PopPK) models in NONMEM using data from Single Ascending Dose (SAD) and Multiple Ascending Dose (MAD) Clinic studies.
  • Perform exposure-response (E-R) analyses linking PK to relevant efficacy, safety, and biomarker endpoints across autoimmune/inflamation indications including Systemic Lupus Erythematosus (SLE), rheumatoid arthritis (RA), Sjögren's syndrome, and dermatomyositis.
  • Translate PopPK/E-R findings into Phase 2 dose and regimen recommendations, presenting quantitative rationale to clinical development and regulatory teams and governance committees.
  • Use R for dataset assembly (e.g., NONMEM-ready datasets), post-processing, diagnostics (goodness-of-fit, VPCs), and reporting of population modeling results.
  • Author and review analysis plans, statistical/pharmacometric analysis reports, and relevant sections of regulatory documents (briefing books, IND/CTA, NDA/BLA modules).

Bioequivalence / Relative Bioavailability & Formulation Bridging

  • Leverage existing PopPK models to conduct bioequivalence (BE) and relative bioavailability analyses supporting introduction of new subcutaneous (SC) formulations, delivery devices, and/or injection sites.
  • Support commercialization readiness for late-stage/marketed assets in autoimmune/inflammation and neuromuscular disease/indications including but not limited to generalized myasthenia gravis (gMG), Chronic Inflammatory Demyelinating Polyneuropathy (CIDP), and Multifocal Motor Neuropathy (MMN) by quantitatively bridging PK across formulation/device/site changes.
  • Design model-based simulation strategies to support waiver arguments or reduced clinical burden for formulation/device bridging studies, in collaboration with CMC, regulatory, and clinical teams.

Cross-Functional & Strategic Contributions

  • Partner with Clinical Development, Research, Translational Medicine, Bioanalytical, Biostatistics, Regulatory Affairs, and CMC to align quantitative strategy with program milestones.
  • Present modeling results and strategic recommendations to senior leadership, IND/NDA teams, and external regulatory agencies as needed.
  • Contribute to health authority interactions (e.g., FDA/EMA meetings) by preparing quantitative pharmacology responses and briefing materials.
  • Oversee CRO pharmacometricians/modelers and contribute to department-wide methodology and process improvements.

Experience

  • Ph.D. in Pharmacometrics, Pharmaceutical Sciences, Clinical Pharmacology, Bioengineering, Systems Biology, or related quantitative discipline (PharmD with relevant pharmacometrics experience also considered).
  • Minimum 6–8 years of relevant industry experience in clinical pharmacology/pharmacometrics, with demonstrated hands-on modeling ownership.
  • Demonstrated proficiency in QSP model development using MATLAB (and modules such as SimBiology or equivalent).
  • Strong hands-on expertise in population PK/PD modeling using NONMEM, including dataset preparation, model diagnostics, and simulation.
  • Proficiency in R for pharmacometric data analysis, visualization, and reporting (e.g., tidyverse, xpose, ggplot2, or similar packages).
  • Experience translating nonclinical and early clinical (SAD/MAD) data into human dose projections and Phase 2 dosing strategies.
  • Experience with bioequivalence/relative bioavailability modeling approaches for formulation, device, or route/site bridging.
  • Familiarity with autoimmune, inflammatory, and/or neuromuscular disease areas (e.g., SLE, Sjögren's syndrome, dermatomyositis, gMG, CIDP, MMN) strongly preferred.
  • Experience authoring pharmacometric sections of regulatory submissions (IND/CTA, briefing documents, NDA/BLA).
  • Excellent written and verbal communication skills, with ability to convey complex quantitative concepts to non-technical stakeholders.

Preferred Qualifications

  • Prior experience supporting subcutaneous biologic formulation/device lifecycle programs.
  • Experience with competitive intelligence modeling and literature-based model informed drug development (MIDD) approaches.
  • Prior direct interaction with FDA/EMA on clinical pharmacology or pharmacometric matters.
  • People management or matrixed team leadership experience.

Originally posted on Himalayas

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