Analysis of Nanoparticle Delivery to Tumors - Wilhelm et. al.ccc.chem.pitt.edu/wipf/Current...
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Analysis of Nanopar.cle Delivery to Tumours
S. Wilhelm, A. J. Tavares, Q. Dai, S. Ohta, J. Audet, H. F. Dvorak, W. C. W. Chan.
Nature Reviews Materials, 2016, 1, 1.
Presented by Alexander ChaJerley
21st of May 2016
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What are Nanopar.cles? • Defined as a parNcle that has a size between 1-‐100 nM. • Have been used unknowingly throughout human history. First
instance being reinforcement of clay with asbestos more than 4500 years ago.
• More recently they have been used to colour glass by the romans in the 4th century and decorate glaze ceramics in Mesopotamia in the 9th century.
Materials Today. 2013, 16, 7, 262.
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What are Nanopar.cles? • One of the first major reports on nanoparNcles was by Michael
Faraday in “Experimental RelaNons of Gold (and other Metals) to Light”.
• Prepared a two phase soluNon of Na[AuCl4]aq and phosphorus in CS2. Observed a colour change from bright yellow to ruby red – consistent with colloidal gold.
Philos. Trans. R Soc. Lond., 147 (1857), 145.
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Synthesis of Nanopar.cles • NanoparNcles come in many forms, popular materials include:
• Silica • Metal oxides • Quantum dots. • Organic polymers and dendrimers.
• Silica nanoparNcles are formed by the hydrolyNc condensaNon of tetraorthosilicate to form parNcles with a controlled size and pore diameters.
• Organic nanoparNcles are formed by emulsion methods.
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Synthesis of Nanopar.cles
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Drug Delivery • Targeted drug delivery first envision by Dr Paul Ehrlich afer
visiNng Maria von Webers opera “Der Freischütz”. • Opera’s antagonist was the “Freikugeln” who always hit their
target. • Envisioned a “Zauberkugeln” or magic bullet that would
always hit its target within the body.
• Another early pioneer was Professor Peter Paul Speiser at ETH Zurich. • Was able to encapsulate proteins and viruses in nanospheres
generated from organic molecules using polymerisaNon.
InternaNonal Journal of PharmaceuNcs, 2007, 331, 1.
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Drug delivery and Cancer • Problem: Majority of cytotoxic chemotherapeu.cs effect both
healthy and malignant .ssues within the body.
• SoluNon: Deliver chemotherapeuNcs directly to malignant Nssues using a smart delivery system (magic bullet).
• How? AJach chemotherapeuNcs to nanoparNcles that can release payload under certain condiNons. • pH • EnzymaNc catalysis • IrradiaNon
Pharmacol Rep. 2012 64(5) 1020.
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This publica.on. • This paper examines the literature concerning nanoparNcle
delivery from the past 10 years.
• It discusses the advances in targeted delivery (or lack thereof).
• Discusses ways of enhancing target selecNvity.
• Proposes a thirty year plan to enhance research.
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Methodology • Authors examined the literature using the following criteria.
• Arrived a 117 publicaNons suitable for examinaNon in this arNcle. • Found that, on average, 0.7% of injected dose (ID) reached the
tumour.
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Data trends
• This average has not significantly changed in the past ten years.
• Inorganic materials provide a higher delivery efficiency than organic (0.8% vs
0.6% ID).
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Data trends
• ParNcles between 10-‐100 nM performed beJer than larger parNcles (0.7% vs
0.6% ID).
• Neutral parNcles tended to have a beJer efficiency than negaNve or posiNve ones (0.7%, 0.6% and 0.5% ID respecNvely).
• Rod shaped parNcles performed the best when compared to spheres, flakes and other shapes. (1.1%, 0.7%, 0.6% and 0.9% ID respecNvely).
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Data trends
• AcNve targeNng methods performed outperformed passive targeNng methods (0.9% vs 0.6% ID).
• Orthotopic allo-‐ and xenografs performed beJer than other methods.
• Higher levels of efficiency shown against cervical, ovarian, pancreaNc and skin cancers.
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Consequences of low delivery efficiency • EvaluaNon for human dose for both an drug encapsulated in a nanoparNcle
and loaded onto the surface.
• AssumpNons: • 60 nM diameter. • Drug has a MW of 500 g/mol-‐1 • IC50 1μM • 1% delivery efficiency • Tumor volume: 0.5 cm3 of a 20g mouse.
• EncapsulaNon: 20% wt of drug encapsulated • 1.2 x 1012 nanoparNcles or 6.5 mg kg-‐1
• Surface loading: 1 drug/nm2 • 2.8 x 1012 or 15.7 mg kg-‐1
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Consequences of low delivery efficiency cont.
Applying this to an average human using a body surface-‐area based dosing strategy: • EncapsulaNon: 20% wt of drug encapsulated
• InjecNon volume of 90 mL
• Surface loading: 1 drug/nm2 • InjecNon volume of 213 mL • Assuming nanoparNcle concentraNon of 5 nM.
• This causes serious problems • Problems synthesising that amount of nanoparNcles. • ProhibiNve cost. • Technical difficulNes due to injecNon volume – higher concentraNons can
impact parNcle stability. • Large quanNty of nanoparNcles may result in toxicity. • Possible that higher volumes than calculated will be required as
nanoparNcles may interact with other components in tumour matrix.
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The Solu.on! The authors propose a soluNon to all of these concerns – raising the average ID efficiency from 1% to 10%. How to do this? • A greater focus on targeted delivery by elucidaNng tumour targeNng
mechanisms.
• Increase mechanisms to evade nanoparNcle clearance.
• Implement a 30 year development plan.
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Nanopar.cle Extravasa.on
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Nanopar.cle Extravasa.on • NanoparNcles are most likely to enter a tumour through the mother vessels via
either intercellular extravasaNon or transcellular extravasaNon.
• Mother vessels leak both plasma and proteins into the tumour through intercellular gaps.
• This results in a very low blood flow, allowing nanoparNcles to cross over due to prolong residence Nme by seeping through the gaps.
• Other transport mechanisms exist such as acNve transport through cells. If one could t a r g e t t h e t r a n s p o r t transcellular mechanisms, it would allow targeted delivery to the tumour. This represents an aJracNve ta rget fo r i n c rea s i ng t he de l i ve r y efficiency.
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Intratumoral Targe.ng Once parNcles have crossed into the tumour matrix they then need to cross into tumour cells. • Problem: Tumour matrix is highly dependent on the type of tumour.
• Solid tumours have a rigid matrix supported by collagen, fibronecNn, fibirin, etc.
• Tumours can have a internal pressure 10-‐40 Nmes greater than normal cells due to poor lymphaNc drainage. This can greatly effect the transport of chemotherapeuNcs within the matrix.
• General consensus is that smaller parNcles penetrate deeper than larger ones.
• Solu.on: A complete and through study of different tumour types and matrices.
• Currently only 2D images are used, full 3D imaging and elucidaNon of nanoparNcle fate is required for further development.
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Nanopar.cle Clearance
NanoparNcles are primarily cleared by the mononuclear phagocyNc system (MPS) and kidneys.
• The MPS system comprises of the following organs: • Liver • Spleen • LymphaNc system • Skin • Bone marrow
Further improvements to delivery efficiency can be made by reducing the clearance ability of these two systems.
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MPS System Macrophagic cells in the liver and spleen engulf nanoparNcles (primarily by phagocytosis) removing them from system circulaNon (similar to first pass metabolism of drugs).
• Large inorganic nanoparNcles can reside in macrophages for extended periods of Nme (possible tox issue?)
• Smaller and organic nanoparNcles are rapidly broken down.
• Larger nanoparNcles are sequestered more rapidly.
• C a N o n i c p a r N c l e s a r e sequestered the fastest follow by anionic parNcles.
• Smaller nanoparNcles circulate through the body more than larger parNcles.
• Possible to overcome these problems using PEG coa.ngs to hide the par.cles.
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Renal clearance NanoparNcles are also filtered by the renal system. • ParNcles smaller than 4-‐6 nM are filtered out of the blood and are eventually
passed in the urine.
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Thirty year plan Despite more than a decade of research and $1 billion, there has been very liJle progress in this field. Many regard a 1% delivery efficiency to be a nonspecific interacNon rather than specific targeNng. • Only a few nanoparNcle formulaNons have been approved – Abraxane and Doxil for
example.
Authors propose a thirty year plan to further develop nanotechnology into a useful force for the treatment of cancer and other disease states.
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Conclusion
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Ques.ons?
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Datasets
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