Jukka Rantanen, Professor PhDjukka.rantanen@sund.ku.dk

Towards commercial scale production of Quality by Design (QbD) based nanomedicine

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OUTLINE

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• Manufacturing sciences – drivers for a change

• Quality by Design (QbD) terminology in the context of nanomedicine

• Snapshot of innovation within manufacturing- digital design of pharmaceutical products- fast analytical tools: combining Raman chemical mapping and image analysis- artificial intelligence (AI) in product design- blockchain of pharmaceutical products

Manufacturing sciences for pharmaceuticals?

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• Typically batch production with a relatively low level of automization

• Process analytics and process control increasingly utilized

• Equipment design “traditional”

• Digital design of pharmaceutical products not in full use

• Acknowledgement of manufacturing sciences

• Translation of nanomedicine innovations and complex pharmaceuticals into products

Continuous manufacturing

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Continuous manufacturing

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Continuous manufacturing

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Continuous vs. Batch processing

* 24/7 processing

Smaller equipment

* factory footprint

More efficient processing

* avoid shortage of medicine

Scale-up

* easier; just increase the time

FUTURE DRIVERS –patient-oriented products

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Precision Medicine Initiative* age, gender* genetics* metabolomics* environment* social media* food * lifestyle

Mass production for an average patient -> Mass personalization for individualized therapies

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Ford assembly line Automated assembly line

Potential with nanomedicine

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Translation of nanomedicine innovations into products:

1. Smaller production geometries, such as microfluidics, enabling continuous production

2. Easier interfacing with primary manufacturing (synthesis)

3. Modular production systems

4. Digital design of production systems

5. Process analytical solutions

6. Integration of pharmaceutical products into the health big data

Manufacturing - nanomedicine

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Colombo et al., 2018. Transforming nanomedicine manufacturing toward Quality by Design and microfluidics. Adv. Drug Del. Rev. 128 115-131.

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Quality by Design QbD terms - nanomedicine

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Colombo et al., 2018. Transforming nanomedicine manufacturing toward Quality by Design and microfluidics. Adv. Drug Del. Rev. 128 115-131.

1. Risk assessment

2. Identify and explore: Quality target product profile (QTPP)-> Critical quality attributes (CQAs)-> Critical material attributes (CMAs)-> Critical process parameters (CPPs)

3. Control strategy

Quality by Design QbD terms – regulatory landscape

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The International Conference on Harmonization (ICH) Quality documents Q8-Q14, https://www.ich.org/products/guidelines/quality/article/quality-guidelines.html

1. Risk assessment

2. Identify and explore: Quality target product profile (QTPP)-> Critical quality attributes (CQAs)-> Critical material attributes (CMAs)-> Critical process parameters (CPPs)

3. Control strategy

Quality by Design QbD terms – nanomedicine

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Quality by Design QbD terms – nanomedicine

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OUTLINE

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• Manufacturing sciences

• Quality by Design (QbD) terminology in the context of nanomedicine

• Snapshot of innovation within manufacturing- digital design of pharmaceutical products- fast analytical tools: combining Raman chemical mapping and image analysis- artificial intelligence (AI) in product design- blockchain of pharmaceutical products

Digital design and computational methods

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Rantanen J. and Khinast J., 2015. The Future of Pharmaceutical Manufacturing Sciences. J. Pharm. Sci. 104 3612-3638

Digital design – classical products

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Boetker J. et al, 2016. In silico product design of pharmaceuticals. Asian J. Pharm. Sci 11 492 -499

Production line Product performance (mechanical/dissolution)

Digital design – nanomedicine production

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Bohr A. et al, 2017. High-throughput Fabrication of Nanocomplexes Using 3D-printed Micromixers. J. Pharm. Sci 106 835–842.

Digital design – molecular dynamics (MD) simulation

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Larsen, A.S. et al., 2017. Tracking dehydration mechanisms in crystalline hydrates with molecular dynamics simulations. Cryst. Growth & Des. 17 5017–5022.

Super cell made from a unit cell 3x10x10

600 naproxen and sodiummolecules/atoms and 1200 water molecules

Digital design – molecular dynamics (MD) simulation

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Raman chemical mapping + image analysis

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Faster analytical tools & processing of data

Model particle systemSekulovic, A. et al., 2020. Unpublished data

Raman chemical mapping + image analysis

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Faster analytical tools & processing of data

Model particle system

Three-step dehydration of theophylline monohydrate (TP MH)

- TP MS1

- TP MS2

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Okeyo, P.O. et al. Imaging of dehydration in particulate matter using Raman line-focus microscopy. Scientific Reports 9, 7525 (2019)

Complexity of dehydration processes

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Okeyo, P.O. et al. Imaging of dehydration in particulate matter using Raman line-focus microscopy. Scientific Reports 9, 7525 (2019)

OUTLINE

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• Manufacturing sciences

• Quality by Design (QbD) terminology in the context of nanomedicine

• Snapshot of innovation within manufacturing- digital design of pharmaceutical products- fast analytical tools: combining Raman chemical mapping and image analysis- artificial intelligence (AI) in product design- blockchain of pharmaceutical products

Artificial intelligence (AI) in product design

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Trnka et al, 2015.

Pharm Dev Technol, 20(1): 65–73

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Artificial intelligence (AI) in product design

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Trnka et al, 2015.

Pharm Dev Technol, 20(1): 65–73

5% w/v mannitol 10% w/v mannitol

Sucrose % w/v

15 10 5 1 0,5 0 15 10 5 1 0,5 0

Pro

tein

load m

g/m

l

35

30

25

20

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Artificial intelligence (AI) in product design

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Trnka, H, 2013. J Pharm Sci 102 4364

Artificial intelligence (AI) in product design

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Trnka, H, 2013. J Pharm Sci 102 4364

Artificial intelligence (AI) in product design

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Trnka, H, 2013. J Pharm Sci 102 4364

QR encoded pharmaceuticals –information-rich products

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KEY ASPECTS

- substrate (‘edible paper’) design - ink composition- information content

QR encoded pharmaceuticals –information-rich products

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Edinger et al., 2018. QR encoded smart oral dosage forms by inkjet printing Int. J. Pharm. 536 138-145

QR encoded pharmaceuticals –information-rich products

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Edinger et al., 2018. Int. J. Pharm. 536 138-145

Information-rich products - BLOCKCHAIN

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• decentralized – cloud

• digital ledger – token – smart contracts

• cryptographically secured chain of blocks

Blockchain of pharmaceutical products

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• cryptopharmaceuticals

• κρυπτοφάρμακα‘kripto’ - hidden place‘farmaka’

• secure chain of pharmaceutical products at a single dosage unit level

Blockchain of pharmaceutical products

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Nørfeldt et al, 2019. Cryptopharmaceuticals: increasing the safety of medication by a blockchain of pharmaceutical products.J. Pharm. Sci. 108 (9): 2838.

Blockchain of pharmaceutical products

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Apple store, MedBlockChain app available free-of-charge since Dec 2018 (Nørfeldt et al)

Nørfeldt et al, 2019. Cryptopharmaceuticals: increasing the safety of medication by a blockchain of pharmaceutical products. J. Pharm. Sci. 108 (9): 2838.

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Apple store, MedBlockChain app available free-of-charge since Dec 2018 (Nørfeldt et al)

Conclusions

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Digital design of pharmaceuticals

Innovative processing solutions & process analytics

Integration of data into the pharmaceutical product

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Prof. Thomas Rades, Holger Grohganz, Korbinian Löbmann,

Anette Müllertz, Jesper Østergaard, Daniel Bar Shalom, Claus Cornett, UCPH

Co-operation

Prof. Andrew Bond, University of Cambridge, UK

Prof. Johannes Khinast, TU Graz/RCPE, AUT

Prof. Lynne Taylor, Purdue University, IN, USA

Prof. Calvin Sun, University of Minnesota, MN, USA

Prof. Thomas de Beer, Ghent University, Belgium

Prof. Niklas Sandler, Åbo Akademi, Finland

Prof. Ben Boyd, Monash University, Australia

Prof. Jukka Rantanen

Assoc. prof. Mingshi Yang, Lene Jørgensen and

Anders Madsen, Natalja Genina

Assistant prof. Adam Bohr, Johan Bøtker

Adjunct prof. Lars Hovgaard (Novo Nordisk)

Adjunct assoc. prof. Poul Bertelsen (Takeda)

Post doc Johanna Aho, Anders Larsen, Stefano Colombo

PhD students Peter Okeyo, Lærke Arnfast, Magnus Edinger, Shuying Ji,

Troels Pedersen, Wanding Lu, Troels Pedersen, Xiaoli Liu, Andrea Sekulovic,

Pernille Qwist Reckey, Anne Linnet Skelbæk-Pedersen, Cosima Hirschberg,

Hjalte Trnka, Nawin Pudasaini

Lab techn. Dorthe Kyed Ørbæk, Pernille Munk Andersen,

Tonnie Skovhus Christiansen

Manufacturing & Materials