Ma lalo o ka piʻi nui ʻana o ka hoʻokūkū e hoʻokūkū i kahi kaiapuni hoʻokele waiwai a me ka ʻenehana, pono e hoʻomau nā ʻoihana lāʻau lapaʻau a me biotech i kā lākou papahana R&D e noho ma mua o ka pāʻani.
Hiki mai nā ʻano hou o waho ma nā ʻano like ʻole a puka mai ma nā wahi like ʻole - mai nā keʻena o ke kulanui, a i nā hui hoʻomaka i kākoʻo ʻia e ka ʻoihana ʻoihana a me nā hui noiʻi ʻaelike (CRO). E nānā kākou i kekahi o nā ʻano noiʻi koʻikoʻi e "wela" i ka makahiki 2018 a ma waho aʻe, a e hōʻuluʻulu i kekahi o nā mea pāʻani koʻikoʻi e hoʻokau nei i nā mea hou.
I ka makahiki i hala, ua hōʻuluʻulu ʻia ʻo BioPharmaTrendkekahi mau mea nuie pili ana i ka ʻoihana biopharmaceutical, ʻo ia hoʻi: kahi holomua o nā ʻano like ʻole o nā ʻenehana hoʻoponopono gene (ka nui, CRISPR/Cas9); he ulu hoihoi ma kahi o ka immuno-oncology (CAR-T cell); ka hoʻonui nui ʻana i ka noiʻi microbiome; ka hoʻonui ʻana i ka hoihoi i ka lāʻau pololei; kekahi mau holomua nui i ka ʻike ʻana i nā lāʻau antibiotic; ke ulu nei ka hauʻoli e pili ana i ka naʻauao akamai (AI) no ka loaʻa ʻana o ka lāʻau lapaʻau / hoʻomohala ʻana; he hoʻopaʻapaʻa akā ulu wikiwiki i ka wahi o ka cannabis lapaʻau; a me ka hoʻomau mau ʻana o ka lāʻau lapaʻau i ke komo ʻana i nā hiʻohiʻona R&D outsourcing e kiʻi i nā mea hou a me ka ʻike.
Aia ma lalo ka hoʻomau o kēia loiloi me nā wahi noiʻi ʻoi aku ka nui o ka noiʻi i hoʻohui ʻia i ka papa inoa, a me kekahi mau manaʻo hoʻonui i nā ʻano i hōʻike ʻia ma luna - inā pili.
1. Hoʻokomo ʻia ʻo Artificial Intelligence (AI) e ka lāʻau lapaʻau a me ka biotech
Me nā hype āpau a puni AI i kēia mau lā, paʻakikī ke kāhāhā i kekahi me kēia ʻano i ka noiʻi lāʻau lapaʻau. Eia nō naʻe, pono e hoʻomaopopo ʻia e hoʻomaka maoli nā ʻoihana i alakaʻi ʻia e AI me ka lāʻau lapaʻau nui a me nā mea pāʻani ʻepekema ola ʻē aʻe, me ka nui o nā hui noiʻi a me nā papahana hui pū -maaneihe papa inoa o nā hana nui i kēia manawa, amaaneihe loiloi pōkole o kekahi mau hana kaulana i ka "AI no ka ʻike lāʻau" i nā mahina i hala.
Ke ʻimi ʻia nei kahi hiki o nā mea hana i hoʻokumu ʻia AI ma nā pae āpau o ka ʻike ʻana a me ka hoʻomohala ʻana i ka lāʻau lapaʻau - mai ka noiʻi ʻana i ka ʻikepili a me ke kōkua ʻana i ka ʻike ʻana a me ka hōʻoia ʻana, i ke kōkua ʻana mai i nā pūhui alakaʻi hou a me nā moho lāʻau lapaʻau, a wānana i kā lākou waiwai a me nā pilikia. A ʻo ka mea hope loa, hiki i ka polokalamu AI-based ke kōkua i ka hoʻolālā ʻana i ka synthesis kemika e loaʻa ai nā pūhui hoihoi. Hoʻohana pū ʻia ʻo AI i ka hoʻolālā ʻana i nā hoʻokolohua pre-clinical a me ka nānā ʻana i ka ʻikepili biomedical a me ka ʻikepili.
Ma waho aʻe o ka loaʻa ʻana o ka lāʻau lapaʻau e pili ana i ka pahuhopu, ua hoʻohana ʻia ʻo AI ma nā wahi noiʻi ʻē aʻe, no ka laʻana, i nā papahana ʻike lāʻau phenotypic - ka nānā ʻana i ka ʻikepili mai nā ʻano ʻike kiʻekiʻe.
Me ka manaʻo nui o nā hoʻomaka ʻana i alakaʻi ʻia e AI i ka ʻike ʻana i ka lāʻau mole liʻiliʻi, aia kekahi hoihoi i ka hoʻohana ʻana i ia mau ʻenehana no ka ʻike ʻana a me ka hoʻomohala ʻana.
2. E hoʻonui ana i nā wahi kemika no ka ʻimi ʻana i ka lāʻau
ʻO kahi ʻāpana koʻikoʻi o nā papahana ʻike lāʻau liʻiliʻi liʻiliʻi ʻo ia ka ʻimi ʻana - ka ʻike ʻana i kēlā mau molekala hoʻomaka e hoʻomaka i kahi huakaʻi i nā lāʻau lapaʻau kūleʻa (ʻaʻole hiki ke ola i kēia huakaʻi, ʻoiai naʻe) - ma o ka nui o ka loiloi, hōʻoia a me nā pae hoʻāʻo.
ʻO ka mea koʻikoʻi o ka ʻimi ʻimi ʻana ʻo ia ke komo ʻana i kahi ākea ākea a me nā kemika o ka lāʻau lapaʻau e like me nā molekala e koho ai i nā moho mai, ʻoi aku hoʻi, no ka hoʻāʻo ʻana i ka biology target novel. Ma muli o ke kūkulu ʻia ʻana o nā hōʻiliʻili pūhui i loaʻa ma ka lima o ka lāʻau lapaʻau ma muli o nā hoʻolālā mole liʻiliʻi e kālele ana i nā pahuhopu olaola i ʻike ʻia, pono nā pahuhopu olaola hou i nā hoʻolālā hou a me nā manaʻo hou, ma kahi o ka hana hou ʻana i ka kemika like.
Ma hope o kēia pono, hana nā keʻena hoʻonaʻauao a me nā ʻoihana pilikino i ka ʻikepili o nā pūhui kemika ma mua o ka mea i loaʻa i nā hōʻiliʻili hui lāʻau maʻamau. ʻO nā hiʻohiʻona he GDB-17 waihona o nā molekala virtual i loaʻa i ka 166,4 billion mole a meFDB-17o 10 miliona mau molekele me he 17 mau ʻātoma kaumaha;ZINKA- he waihona manuahi o nā pūhui i loaʻa i nā mea kūʻai aku no ka hoʻomaʻamaʻa ʻana i ka virtual, i loaʻa iā 750 miliona mau mole, me 230 miliona ma nā ʻano 3D i mākaukau no ka hoʻopaʻa ʻana; a me ka hoʻomohala hou ʻana o REadily AvailabLe (REAL) wahi kemika e Enamine — 650 miliona mau moleke hiki ke huli ʻia ma oMea hoʻokele lewa REALlako polokalamu, a337 miliona mole e ʻimi ʻia(ma ka like) ma EnamineStore.
ʻO kahi ala ʻē aʻe e hiki ai ke komo i ka wahi kemika e like me ka lāʻau hou no ka ʻimi ʻimi ʻana i ka hoʻohana ʻana i ka ʻenehana waihona puke DNA-encoded (DELT). Ma muli o ke ʻano "split-and-pool" o ka DELT synthesis, hiki ke hana i ka nui o nā pūhui ma ke ʻano kumu kūʻai a me ka manawa kūpono (miliona a i nā piliona o nā pūhui).EiaHe hōʻike ʻike e pili ana i ka mōʻaukala, nā manaʻo, nā kūleʻa, nā palena, a me ka wā e hiki mai ana o ka ʻenehana waihona DNA-encoded.
3. Huli i ka RNA me nā mole liʻiliʻi
He ʻano wela kēia i ka wahi ʻike lāʻau me ka ulu mau ʻana o ka hauʻoli: ʻoi aku ka ikaika o nā mea hoʻonaʻauao, nā ʻoihana biotech a me nā hui lāʻau lapaʻau e pili ana i ka huli ʻana i ka RNA, ʻoiai ke kiʻekiʻe nei ka maopopo ʻole.
I loko o ke kino ola,DNAmālama i ka ʻike nopūmuahoʻohuihui aRNAlawe i nā ʻōlelo kuhikuhi i hoʻopaʻa ʻia i ka DNA e alakaʻi ana i ka synthesis protein i loko o nā ribosomes. ʻOiai ʻo ka hapa nui o nā lāʻau lapaʻau e kuhikuhi ʻia i ka huli ʻana i nā protein e pili ana i kahi maʻi, i kekahi manawa ʻaʻole lawa ia e kāohi i nā kaʻina pathogenic. Me he mea lā he hoʻolālā akamai e hoʻomaka mua i ke kaʻina hana a hoʻoikaika i ka RNA ma mua o ka hoʻohui ʻia ʻana o nā proteins, no laila e hoʻohuli nui i ke kaʻina unuhi o ka genotype i ka phenotype makemake ʻole (hōʻike maʻi).
ʻO ka pilikia, ʻo nā RNAs he mau pahuhopu weliweli loa no nā molekole liʻiliʻi - he laina laina, akā hiki ke wili, pelu, a pili paha iā ia iho, me ka hāʻawi maikaʻi ʻana i kona ʻano i nā ʻeke paʻa kūpono no nā lāʻau lapaʻau. Ma waho aʻe o kēia, ʻokoʻa i nā protein, ua haku lākou i ʻehā mau poloka hale nucleotide e ʻano like a paʻakikī hoʻi no ke koho ʻana e nā molekole liʻiliʻi.
Eia naʻe,he mau mea holomua i hala iho neimanaʻo e hiki maoli ke hoʻomohala i nā molekole liʻiliʻi e like me ka lāʻau lapaʻau e hoʻoikaika i ka RNA. ʻO nā ʻike ʻepekema hou i alakaʻi i ka wikiwiki gula no RNA -ma ka liʻiliʻi he kakini huiLoaʻa nā papahana i hoʻolaʻa ʻia iā ia, me ka lāʻau lapaʻau nui (Biogen, Merck, Novartis, a me Pfizer), a me nā hoʻomaka biotech e like me Arrakis Therapeutics me kahi$38M Pūʻali A punii 2017, a me Expansion Therapeutics -$55M Series A ma mua o 2018.
4. Loaʻa nā lāʻau antibiotic hou
Ke ulu nei ka hopohopo e pili ana i ka piʻi ʻana o nā maʻi maʻi antibiotic - superbugs. ʻO lākou ke kuleana no kahi o 700,000 mau make ma ka honua holoʻokoʻa i kēlā me kēia makahiki, a e like me ka loiloi aupuni UK hiki ke piʻi nui kēia helu - a hiki i ka 10 miliona ma 2050. Hoʻomaka ka bacteria a hoʻomohala i ke kū'ē i nā lāʻau antibiotic i hoʻohana maʻamau me ka lanakila nui, a laila lilo i makehewa me ka manawa.
ʻO ke kuhikuhi ʻana i nā lāʻau antibiotic e mālama i nā hihia maʻalahi i nā maʻi a me ka hoʻohana nui ʻana i nā lāʻau antibiotic i ka mahiʻai holoholona e hoʻopilikia i ke kūlana ma ka hoʻonui ʻana i ka nui o nā mutation bacteria, e hoʻolilo iā lākou i kū i nā lāʻau me ka wikiwiki weliweli.
Ma ka ʻaoʻao ʻē aʻe, ʻo ka loaʻa ʻana o nā lāʻau antibiotic he wahi maikaʻi ʻole no ka noiʻi lāʻau lapaʻau, ke hoʻohālikelike ʻia me ka hoʻomohala ʻana i nā lāʻau 'economically feasible'. ʻO ia paha ke kumu nui ma hope o ka maloʻo ʻana o ka pipeline o nā papa antibiotic hou, me ka mea hope i hoʻolauna ʻia ma mua o kanakolu makahiki i hala.
I kēia mau lā ke lilo nei ka ʻike antibiotic i wahi ʻoi aku ka maikaʻi ma muli o kekahi mau hoʻololi maikaʻi i ka ʻaha ʻōlelo hoʻoponopono, hoʻoulu i ka lāʻau lapaʻau e ninini kālā i loko o nā papahana ʻike antibiotics, a me nā mea hoʻopukapuka kālā - i nā hoʻomaka biotech e hoʻomohala ana i nā lāʻau lapaʻau antibacterial. I ka makahiki 2016, kekahi o mākou (AB)nānā i ke kūlana o ka loaʻa ʻana o ka lāʻau antibiotica hōʻuluʻulu i kekahi o nā hoʻomaka hoʻohiki i ka lewa, me ka Macrolide Pharmaceuticals, Iterum Therapeutics, Spero Therapeutics, Cidara Therapeutics, a me Entasis Therapeutics.
ʻO ka mea nui, ʻo kekahi o nā mea hōʻeuʻeu hou loa i ka wahi antibiotic ʻo ia kaʻike ʻia ʻo Teixobactina me kāna mau analogs ma 2015 e kahi hui o nā ʻepekema i alakaʻi ʻia e Kauka Kim Lewis, Luna Hoʻokele o ka Antimicrobial Discovery Center ma Northeastern University. Manaʻo ʻia kēia ʻano lāʻau antibiotic hou ikaika e hiki ke kū i ka hoʻomohala ʻana i ke kūʻē ʻana i ka maʻi bacterial. I ka makahiki i hala aku nei, ua hoʻomohala nā mea noiʻi mai ke Kulanui o Lincoln i kahi mana synthesized o teixobactin, e hana ana i kahi hana nui i mua.
I kēia manawa ua hōʻike nā mea noiʻi mai Singapore Eye Research Institute i ka mana synthetic o ka lāʻau lapaʻau hiki ke hoʻōla maikaʻi i ka Staphylococcus aureus keratitis i nā hiʻohiʻona ʻiole ola; ma mua o ka hana o teixobactin i hōʻike wale ʻia i loko o ka vitro. Me kēia mau ʻike hou, pono ʻo teixobactin i kahi 6-10 mau makahiki o ka hoʻomohala ʻana e lilo i lāʻau lapaʻau e hiki ai i nā kauka ke hoʻohana.
Mai ka loaʻa ʻana o ka teixobactin i ka makahiki 2015, ua loaʻa kekahi ʻohana hou o nā lāʻau lapaʻau i kapa ʻia he malacidins.i hōʻike ʻia i ka makahiki 2018. Aia kēia ʻike i ka wā mua, ʻaʻole kokoke i hoʻomohala ʻia e like me ka noiʻi hou loa e pili ana i ka teixobactin
5. Nānā Phenotypic
ʻAe kiʻi:SciLifeLab
Ma 2011 nā mea kākau ʻo David Swinney lāua ʻo Jason Anthonypaʻi ʻia nā hopena o kā lākou ʻikee pili ana i ka loaʻa ʻana o nā lāʻau lapaʻau hou ma waena o 1999 a me 2008 me ka wehe ʻana i ka ʻoiaʻiʻo ua ʻike maoli ʻia nā lāʻau lapaʻau liʻiliʻi liʻiliʻi mua i ka hoʻohana ʻana i ka phenotypic screening ma mua o nā ala i hoʻokumu ʻia (28 mau lāʻau i ʻae ʻia me 17, kēlā me kēia) - a ʻoi aku ka maikaʻi o ka noʻonoʻo ʻana ʻo ia ke ʻano i hoʻokumu ʻia i ka pahuhopu i manaʻo nui ʻia i ka wā i ʻōlelo ʻia.
Ua hoʻomaka kēia loiloi koʻikoʻi i ka renaissance o ka phenotypic drug discovery paradigm mai 2011 - ma ka ʻoihana lāʻau lapaʻau a ma ke kula. ʻO ka mea i hala aku nei, nā kānaka ʻepekema ma Novartishana i ka loiloiʻO ke kūlana o kēia ʻano a hiki i ka hopena, ʻoiai ʻo nā hui noiʻi lāʻau lapaʻau i loaʻa i nā pilikia nui me ke ʻano phenotypic, aia ka emi ʻana o nā pale e pili ana i ka pahuhopu a me ka piʻi ʻana o nā ala phenotypic i nā makahiki 5 i hala. ʻO ka hapa nui, e hoʻomau ʻia kēia ʻano ma mua o 2018.
ʻO ka mea nui, ma waho aʻe o ka hoʻohālikelike ʻana i nā ʻano phenotypic a me ka hoʻokumu ʻana i ka pahuhopu, aia kahi ʻano maʻalahi i ka hoʻāʻo ʻana i nā kelepona paʻakikī, e like me ka hele ʻana mai nā laina kelepona make ʻole i nā cell mua, nā cell maʻi, co-culture, a me nā moʻomeheu 3D. Ke hele nei ka hoʻonohonoho hoʻokolohua ma mua o nā heluhelu univariate no ka nānā ʻana i nā loli i nā keʻena subcellular, ka nānā ʻana o ka cell cell a me ke kiʻi kelepona.
6. Okana (kino)-ma-a-chip
Hiki i nā microchips i hoʻopaʻa ʻia e nā mea ola kanaka ke hoʻololi i ka hoʻomohala ʻana i ka lāʻau lapaʻau, ka hoʻohālikelike ʻana i nā maʻi a me nā lāʻau lapaʻau pilikino. ʻO kēia mau microchips, i kapa ʻia ʻo 'organs-on-chips', hāʻawi i kahi koho kūpono i ka hoʻāʻo holoholona kuʻuna. ʻO ka hope loa, ʻo ka hoʻohui ʻana i nā ʻōnaehana holoʻokoʻa he ala ia e loaʻa ai ka ʻōnaehana holoʻokoʻa "body-on-a-chip" kūpono no ka ʻike ʻana i ka lāʻau a me ka hoʻāʻo ʻana a me ka hōʻoia ʻana o ka moho lāʻau.
He mea nui kēia ʻano i ka loaʻa ʻana o ka lāʻau lapaʻau a me ka hoʻomohala ʻana a ua uhi mākou i ke kūlana o kēia manawa a me ka pōʻaiapili o ka paradigm "organ-on-a-chip" i kēia manawa.hōʻike liʻiliʻi.
ʻOiai ka nui o nā kānalua i loaʻa ma kahi o 6-7 mau makahiki i hala aku nei, i ka wā i haʻi ʻia ai nā manaʻo ma ke kula e nā mea hoʻokipa hoihoi. I kēia lā naʻe, ʻike ʻia ka poʻe hoʻohewa i ka hoʻi hope. ʻAʻole wale nā ʻoihana hoʻoponopono a me ke kālāapo i ka manao, akā, ke mahuahua neihāpai ʻiama ke ʻano he kahua noiʻi lāʻau lapaʻau e ka lāʻau lapaʻau a me ke kula. Ua hōʻike ʻia ma luna o ʻelua kakini ʻōnaehana okana i nā ʻōnaehana on-chip. E heluhelu hou e pili ana ia meamaanei.
7. Bioprinting
Ke ulu wikiwiki nei ka wahi o ka bioprinting i nā ʻiʻo a me nā kino kanaka a ʻo ia, ʻaʻohe kānalua, ka lāʻau lapaʻau e hiki mai ana. Hoʻokumu ʻia i ka hoʻomaka ʻana o 2016,Cellinkʻo ia kekahi o nā hui mua o ka honua e hāʻawi i ka bioink paʻi 3D - he wai e hiki ai ke ola a me ka ulu ʻana o nā cell kanaka. I kēia manawa, hana ka hui i nā ʻāpana o ke kino - nā ihu a me nā pepeiao, ka mea nui no ka hoʻāʻo ʻana i nā lāʻau lapaʻau a me nā mea hoʻonaninani. Paʻi pū ʻo ia i nā cubes e hiki ai i nā mea noiʻi ke "pāʻani" me nā cell mai nā kino kanaka e like me nā ate.
Ua hui pū ʻo Cellink me CTI Biotech, he hui lapaʻau Farani i hana kūikawā i ka hana ʻana i nā ʻiʻo maʻi maʻi, i mea e holomua nui ai i ka wahi o ka noiʻi maʻi maʻi a me ka ʻike ʻana i ka lāʻau.
ʻO ka hoʻomaka ʻana o ka biotech ʻōpio e kōkua maoli iā CTI i ka paʻi 3D i nā kope o nā maʻi maʻi kanesa, ma o ka hui ʻana i ka bioink o Cellink me kahi laʻana o nā maʻi maʻi maʻi. E kōkua kēia i nā mea noiʻi i ka ʻike ʻana i nā lāʻau lapaʻau hou e kūʻē i nā ʻano maʻi kanesa.
ʻO kekahi mea hoʻomaka biotech e hoʻomohala ana i ka ʻenehana paʻi 3D no ka paʻi ʻana i nā mea olaola - kahi hui spinout o Oxford University, OxSyBio, kahiua hoʻopaʻa wale ʻia ʻo £10mi ke kālā Series A.
ʻOiai ʻo 3D bioprinting he ʻenehana maikaʻi loa ia, paʻa a ola ʻole no ka mea e noʻonoʻo ana i ke kūlana mua o ka mea i paʻi ʻia. ʻO ke ala ʻoi aku ka holomua o ka hoʻokomo ʻana i ka "manawa" ma ke ʻano ʻehā o nā mea bio-mea i paʻi ʻia (i kapa ʻia ʻo "4D bioprinting"), hiki iā lākou ke hoʻololi i ko lākou ʻano a i ʻole nā hana me ka manawa e kau ʻia ai kahi hoʻoulu ʻana o waho.Eiahe loiloi ʻike no ka 4D bioprinting.
Kuanaʻike pani
ʻOiai me ka luʻu ʻole ʻana i kēlā me kēia o nā ʻano kiʻekiʻe i hōʻike ʻia, pono e ʻike ʻia e lawe ʻo AI i kahi ʻāpana o ka hana. ʻO kēia mau wahi hou o ka biopharma innovation ua lilo i mea kikowaena data nui. Ke hōʻike nei kēia kūlana i kahi kūlana koʻikoʻi no AI, me ka ʻike pū ʻana, ma ke ʻano he postscript i kēia uhi o ke kumuhana, aia ʻo AI i nā mea hana he nui, analytical a me nā helu e hoʻomau mau nei i ka hoʻomohala ʻana. ʻO nā noi o AI i ka ʻike ʻana i ka lāʻau lapaʻau a me ka hoʻomohala mua ʻana no ka hapa nui i ka wehe ʻana i nā hiʻohiʻona huna a me nā manaʻo e pili ana i nā kumu a me nā hopena inā ʻaʻole ʻike ʻia a hoʻomaopopo ʻia.
No laila, ʻoi aku ka maikaʻi o ka subset o nā mea hana AI i hoʻohana ʻia i ka noiʻi lāʻau lapaʻau ma lalo o ka moniker o "machine intelligence" a i ʻole "machine learning". Hiki ke mālama ʻia kēia mau mea e ke alakaʻi kanaka, e like me nā papa helu a me nā ʻano aʻo helu helu, a i ʻole ka mālama ʻole ʻia i kā lākou hana i loko e like me ka hoʻokō ʻana i nā ʻano ʻenehana neural artificial. ʻO ka ʻōlelo a me ka hoʻoponopono semantic a me nā ʻano probabilistic no ka noʻonoʻo maopopo ʻole (a i ʻole fuzzy).
ʻO ka hoʻomaopopo ʻana pehea e hiki ai ke hoʻohui ʻia kēia mau hana like ʻole i loko o ke aʻo ākea o "AI" he hana koʻikoʻi ia e pono ai nā poʻe makemake āpau e hana. ʻO kahi o nā wahi maikaʻi loa e ʻimi ai i nā wehewehe a me nā wehewehe ʻana ʻo ia kaWaena ʻEpekema ʻIkepiliportal a ʻoi aku ka nui o nā pou blog na Vincent Granville, nāna i mauwehewehe i nā ʻokoʻama waena o AI, hilinaʻi mīkini, aʻo hohonu, a me nā helu. ʻO ka lilo ʻana i kamaʻilio ʻana i ka ins a me waho o AI ma ke ʻano holoʻokoʻa he mea koʻikoʻi ia o ka mālama ʻana a i ʻole ma mua o nā ʻano biopharma.
Ka manawa hoʻouna: Mei-29-2018