Factory of the Future - Janssen Pharmaceutica Case Study

It is not a surprise to hear that the pharmaceutical industry is under pressure. Many countries are cutting their health care budget resulting in reduced prices and reimbursement rates. This evolution negatively affects gross profits and sales volumes. Increased competition takes place due to generic companies aggressively seeking to extend their market share.

The R&D success rate of ethical pharmaceutical companies is substantially decreasing while patent protection of block busters of the ‘90’s is slowly but surely fading away. All these factors lead to declining company revenues while increased R&D budgets are required to keep up R&D success rates of the past.

This requires each entity of a company to drastically increase its efficiency. Product Development will need to find ways to speed up development and transfer. The Supply Chain entity as a result will need to reduce costs, improve production economics and increase manufacturing flexibility. Continuous processing technologies can play an important role in achieving these challenging objectives.

Background

When the interest in continuous manufacturing started to emerge in the pharmaceutical industry, Janssen Pharmaceutica was one of the pioneers to investigate its potential. In their attempt to evaluate the market of OSD continuous manufacturing technology, a project team within Global Technical Services was put in place to prepare the company for a science- and risk-based strategic decision in favour of this innovative manufacturing technology and to select the most appropriate technology and vendor.

Janssen Pharmaceutica decided to spend substantial attention to the new continuous high shear wet granulation and drying technology of GEA Pharma Systems, ConsiGma™ as one of the technologies in the market with much potential.

The team initiated an in-depth feasibility study to build a strong understanding of capabilities and constraints of ConsiGma™ technology and process. The team understood a strong business case is needed to convince top management to switch from current manufacturing techniques (of which there is overcapacity in the Supply Chain) to this innovative way of producing tablets.

To support the business case, they selected a formulation which is representative for the portfolio of formulations using conventional fluid bed granulation batch process. In addition, the immediate release character of the tablet and BCS class 1 of the API’s involved enable the team to apply for a bio-waiver provided dissolution profile is similar or identical to the one of the batch-produced product.

The business case aims at proving the business value of the new technology in 4 areas: time, quality cost, and agility.

Using continuous processing, it is expected that process development will be much faster, thanks to more efficient Design of Experiments. Also tech transfer will be faster, as scale-up and process transfer is reduced. Cycle time, as last element related to the time perspective, is expected to be shorter thanks to elimination of intermediate storage between unit operations.

From a quality perspective, a much more intensive process monitoring and control will allow us to proactively address process excursions and therefore run a more stable and consistent process. Supply chain reliability will be the logical benefit.

Cost reductions are expected in a number of areas, such as development, investment, QC and inventory. The faster development and reduced scale-up efforts will impact the cost of development, while the small footprint of the equipment will reduce investment costs. On-line monitoring and real-time release testing will reduce QC costs and elimination of intermediate storage reduces inventory costs. Last but not least, the less labour-intensive operation of this new technology will have an impact on conversion costs.

Finally, thanks to the flexibility of the technology, both in batch size and in process technology, as well as the ability to easily reconfigure and relocate the line, business value is expected from an agility perspective.

Trial Runs

Before the extensive trials for the business case could commence, optimal production parameters for this formulation on ConsiGma™ needed to be determined.

This was the first test case for the claim that ConsiGma™ would provide business value from a time perspective by reducing process development time.

Using a Design of Experiments approach, the optimal production parameters for this formulation were found in a relatively short number of trials, with a limited amount of product (using 150 kg of product).

After defining the optimal parameters, process stability was proven during a number of long runs. The trial started with a 10 hour run, was followed by 3 repeat runs of approximately 5 hours to prove repeatability and reproducibility and was concluded with a 16 hour run to assess overall performance incl. the online measurement techniques.

Online Measurements

For this feasibility study, the system is equipped with 4 online measurement tools to measure Critical Quality Attributes (moisture measurement, particle size, blend uniformity and content uniformity) in the process line.

All of the used online tools for this project are optical systems and hence keeping the observation windows clean during the longer production runs is critical. For both the NIR based systems, GEA’s own patented LightHouse Probe™ technology was used. They were programmed to wash the observation window every half hour. The first LHP, in combination with a filter wheel based sensor (NDC) measured the moisture content of the product prior to the milling step. The second LHP was mounted above the tablet press to check blend uniformity and Magnesium Stearate mixing just before the product entered the press. A diode array spectrometer (J&M) is connected to the probe to ensure fast measurement cycles needed to achieve a good representative sample mass.

LightHouse Probe™ technology

Figure 2. LightHouse Probe™ technology

Next to these two probes, an on-line laser diffraction measurement system (X-Optix) was installed below the mill to monitor the particle size distribution after that production step. And finally, samples of the produced tablets were analyzed using a Bruker TANDEM after the press to obtain information about the content uniformity.

Bruker TANDEM

Figure 3. Bruker TANDEM

The data flow of all these systems was coordinated by a SIPAT® system of SIEMENS that allowed online visualization of the used spectrometers.

Location of the online measurement systems: 1.Moisture content, 2. Particle Size, 3.Blend Homogeneity, 4.Content uniformity

Figure 4. Location of the online measurement systems: 1.Moisture content, 2. Particle Size, 3.Blend Homogeneity, 4.Content uniformity

Results

All process data and tablet QC data available for all long runs have been thoroughly analyzed to assess process stability and robustness. The review of process data allowed the team to confirm the stability of the process and to evaluate process sensitivity to minor changes in environmental conditions. The good correlation between process data and tablet QC data enabled the team to confirm process parameter settings and ranges and hence to demonstrate process robustness. The repeat long runs helped the team to build satisfactory understanding about process and product behaviour at start-up, during routine operation and at shutdown and to obtain a preliminary idea about potential process capability. Some data are reported in the figures shown following.

Process robustness during 10 h run

Figure 5. Process robustness during 10 h run

The measured CQA’s during a 16 hours run (weight, thickness and content uniformity), extracted from SIPAT®.

Figure 6. The measured CQA’s during a 16 hours run (weight, thickness and content uniformity), extracted from SIPAT®.

Conclusions

Current status of the feasibility study allows the team to confirm already some of the business values set forward in the business case.

Using the ConsiGma™ technology, process development can be done in a very short time. Assuming development and commercial manufacturing is done on the ConsiGma™ 25 line, technology transfer has become redundant, resulting in a substantial time-to-market reduction. Cost of development will decrease accordingly.

The agility of the system, thanks to the flexible process technology, has been proven during process development resulting in effective and efficient design of experiments.

Process stability and robustness has been proven by those different long runs (between 1 and 16 hrs) during which tablets of consistent quality have been produced.

Real-time, in-line measurements have shown their ability to monitor the process based on predetermined intermediate and finished product attributes and to detect minor changes in these attributes’ values. They represent a promising infrastructure allowing to monitor and control the process as well as to introduce real-time-release testing.

This information has been sourced, reviewed and adapted from materials provided by Bruker Optics.

For more information on this source, please visit Bruker Optics.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Bruker Optics. (2021, March 05). Factory of the Future - Janssen Pharmaceutica Case Study. AZoM. Retrieved on October 14, 2024 from https://www.azom.com/article.aspx?ArticleID=7111.

  • MLA

    Bruker Optics. "Factory of the Future - Janssen Pharmaceutica Case Study". AZoM. 14 October 2024. <https://www.azom.com/article.aspx?ArticleID=7111>.

  • Chicago

    Bruker Optics. "Factory of the Future - Janssen Pharmaceutica Case Study". AZoM. https://www.azom.com/article.aspx?ArticleID=7111. (accessed October 14, 2024).

  • Harvard

    Bruker Optics. 2021. Factory of the Future - Janssen Pharmaceutica Case Study. AZoM, viewed 14 October 2024, https://www.azom.com/article.aspx?ArticleID=7111.

Ask A Question

Do you have a question you'd like to ask regarding this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.