# Pawel Olszowy

Pawel Olszowy writes about pharmaceutical manufacturing, with a focus on analytical development, process understanding, and planning regulatory changes across a product’s lifecycle. The posts discuss work at Polpharma API, including process analytical technology, impurity control, and GMP scale-up for complex drug components.

- Profile: https://b2binfluencer.marketing/creators/pawel-olszowy/
- LinkedIn: https://www.linkedin.com/in/pawel-olszowy-72a92b26
- LinkedIn followers: 1,439
- Topics: email-marketing
- Based on 10 dated posts, latest 2026-10-07

## Summary

They are useful for explaining complex pharmaceutical manufacturing processes and regulatory planning to a specialist audience.

- Best for: Brands focused on pharmaceutical manufacturing, CMC, or regulatory services seeking technical credibility.
- Not for: Consumer health brands or software vendors seeking broad reach or simple product endorsements.
- Check first: Confirm audience role, engagement data, and specific results for technical topics.

### Takeaways

- A passing release test does not prove the process is under control.
- Process analytical technology requires validated models and system integration.
- Regulatory flexibility should be planned during the development stage.

## Main ideas

- **Plan for post-approval change during development**: Pawel Olszowy argues that waiting until after approval to consider post-approval changes is too late. They see ICH Q12’s main advantage in designing flexibility into a product before the first commercial batch is released—not in speeding up variations. Three tools underpin the argument: Established Conditions identify which dossier elements are critical to product quality and which can be managed through the Pharmaceutical Quality System; Post-Approval Change Management Protocols let a company agree with regulators in advance on the data, studies, and acceptance criteria for future manufacturing changes; and a Product Lifecycle Management document turns those commitments into a living commercial lifecycle roadmap. Site transfers, supplier qualifications, capacity increases, process optimization, and supply-chain resilience all come after approval, so companies are better placed to manage them if they plan early. At Polpharma, they say, lifecycle management is part of development.
- **A passing release test does not prove the process is under control**: Pawel Olszowy calls the belief that a passing release test proves a well-controlled process the most dangerous illusion in pharmaceutical manufacturing. End-product testing confirms batch quality, but does not explain where an impurity formed, why it formed, whether the process stayed in control throughout manufacturing, or whether the next batch will behave the same way. They advocate tracing impurities’ origin, fate, and purge across the process, then defining critical process parameters around impurity formation, designing meaningful in-process controls, demonstrating impurity purge scientifically, and treating end-product testing as confirmation rather than the primary safeguard. Digital twins and model-based process development, they say, can help teams test process choices before locking in a process.
- **Treat process analytical technology as a multiyear operating change, not a tool purchase**: Pawel Olszowy presents PAT as more than a set of instruments: it signals a shift in small-molecule manufacturing from retrospective quality control to real-time insight. In-line and at-line tools monitor critical quality attributes during synthesis, granulation, and tableting. But effective implementation, they argue, depends on validated analytical models, robust integration with platforms such as LIMS and MES, and cross-functional ownership across R&D, manufacturing, and QA. They say implementation often takes years, not months. The benefits they cite include faster, more confident batch-release decisions; earlier detection of process deviations; less rework and material loss; and more consistent technology transfer between sites. At Polpharma API, they describe PAT as part of a broader transformation that increasingly embeds process data, automation, and advanced monitoring in development and production.
- **Analytical development underpins complex manufacturing programs**: In a collaboration announcement, Pawel Olszowy says Polpharma API will support GMP scale-up and manufacturing of an MMAE-based payload–linker for an ADC program with Celon Pharma S.A. They use the project to argue that analytical development gives process development and manufacturing teams the understanding to make informed decisions. For complex payloads, linkers, and payload–linkers, that means profiling impurities, developing robust analytical methods, confirming process consistency, and building the knowledge needed for scale-up and GMP manufacturing. They say a strong analytical foundation is essential to turning innovative science into a manufacturing-ready therapy.
- **Their recurring priority is designed-in control, not after-the-fact confirmation**: Across the posts, Pawel Olszowy returns to one principle: decisions made earlier in development are stronger than artifacts produced later. ICH Q12 helps design flexibility in before approval; impurity control requires explaining impurity formation and purge, not merely passing a release test; and PAT delivers value when built into validated models and operating ownership, not simply installed. Each post moves from a misconception or question to a framework and its practical manufacturing consequences. The focus is on development decisions, not documents, tests, or tools.

## Work to read

- [The most dangerous illusion in pharmaceutical manufacturing](https://www.linkedin.com/posts/pawel-olszowy-72a92b26_the-most-dangerous-illusion-in-pharmaceutical-activity-7503029654446948353-LUhd)
- [Thinking about post-approval changes after approval? That's already too late](https://www.linkedin.com/posts/pawel-olszowy-72a92b26_thinking-about-post-approval-changes-after-activity-7478021367209070592-pF__)
- [New collaboration with Celon Pharma on an ADC payload–linker program](https://www.linkedin.com/posts/pawel-olszowy-72a92b26_im-pleased-to-share-that-in-our-new-collaboration-activity-7495066597242445824-A76P)
- [Is Process Analytical Technology just a set of analytical tools?](https://www.linkedin.com/posts/pawel-olszowy-72a92b26_is-process-analytical-technology-just-a-set-activity-7457008182092234752-PqtL)

## Brand relationships

- **Polpharma API** (employment)
- **Celon Pharma S.A.** (disclosed_partnership)

## Partnerships

Pawel Olszowy’s posts focus on pharmaceutical manufacturing and analytical development, covering impurity control and digital twins, ICH Q12 lifecycle planning, process analytical technology implementation, and Polpharma API’s analytical work. One post announces a collaboration between Polpharma API and Celon Pharma on GMP scale-up and manufacturing of an MMAE-based payload-linker for an ADC program. It describes a company-to-company manufacturing agreement, not a creator sponsorship offer. No sponsorship formats, brand-collaboration terms, rates, or partnership inquiry route are published. Before planning, a brand should ask directly about available formats, usage rights, review cycles, disclosure practices, rates, and how to inquire about partnerships.

## Alternatives

- Dr. Naeem Gulzar: Choose Dr. Naeem Gulzar when the campaign is about getting a formulated product into reproducible production, not pharmaceutical process development or regulatory strategy. Two posts describe coordinating product development, sales and marketing, production, quality control, regulatory, and purchasing to take skincare and suncare formulations from laboratory work to full production at KLG Liquida, part of the KLAPP Skin Care Science group. They cover a customer approving a formulation after a single sampling round, supplier discussions when standard ordering was not enough, and intermediate scale-up trials with reference samples and laboratory support during production. Gulzar is the better choice for campaigns seeking a first-person account of cross-functional teamwork, short-cycle launches, and shop-floor problem solving in personal care—told in a register marketing teams can reuse without heavy editing. The posts answer whether this person can speak credibly about the process through coordination detail, rather than analytical or regulatory depth.
- Santi Adavani: Choose Santi Adavani when the campaign is about digital twins, simulation, and Industry 4.0 adoption across manufacturing, rather than a specific drug process or regulatory pathway. The posts cover production scheduling, bottleneck identification that spreadsheets miss, layout testing before construction, predictive maintenance, workforce planning, and a staged maturity model from descriptive twins upward, including automotive asset modelling, engineering design simulation, and VR showrooms. They name the data sources a factory twin draws on, such as PLC, MES, and IoT feeds, inventory levels, demand forecasts, and maintenance logs, and give adoption figures. That structure suits an educational post for operations or digital-transformation leaders deciding where to start, and travels across manufacturing sectors. Adavani is the better choice when campaign reach extends beyond pharmaceuticals or the message is about technology adoption rather than process understanding.
- David Katzman: Choose David Katzman when the campaign targets product development software and engineering decision-makers, rather than pharmaceutical process and regulatory work. The posts are release- and milestone-driven: a cloud-native design and simulation workflow built with NVIDIA for robotics teams, a cloud-native model-based definition capability, an AI advisor embedded in the design environment, PLM for regulated industries on government cloud, integrations between PCB design and mechanical CAD, and an annual roundup of customer adoption, a new Melbourne office, and a Gartner positioning. A second post introduces a platform release for connecting systems, automating workflows, and keeping product data moving across the lifecycle. This suits campaigns aimed at buyers seeking a vendor-side view of product development tooling and a message tied to software capabilities and roadmap, with an audience of engineering and IT leadership in discrete manufacturing.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/