Canget BioTekpharma LLC
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Technology
Major IP
Drug Pipeline
AI and FL118 Platform Precision Medicine
Cancer is a complex genetic and epigenetic disease with high genetic instability. Specifically, cancer has multiple gene mutations, aberrant expression and/or alterations (e.g. amplification, deletion, etc.). Some of the universal changes in cancer involving treatment resistance includes (but not limited to) overexpression and/or contitutive activation of antiapoptotic and oncogenic proteins (e.g. survivin, Mcl-1, MdmX, mutant Kras), DNA repair regulators (e.g. ERCC1/6) and efflux pump proteins (e.g. ABCG2/BCRP, Pgp/MDR-1) as well as the loss of tumor suppressor activity (e.g. p53 mutation). The other characteristic of cancer is its heterogeneity where even in the same cancer type or even in the same patient’s tumor at different tumor locations, the cancer molecular profile can be different. Therefore, personalized precision medicine by targeting a particular genetic mutation or epigenetic changes at a particular point in a time (usually at diagnosis) for cancer, would not be sufficient to control cancer, especially for the advanced cancer with metastasis. Two options may resolve the complicated cancer sitution. Either one drug to target and bypass multiple cancer treatment resistance mechanisms or to use multiple drugs through combination treatment. However, the multiple drug combinaiton treatment approach is likely to result in a serious toxicity side effect issue. Thus, the former strategy is the most desirable and ideal strategy if it can be realized. The technology owned by Canget matches this situation.

The lead antitumor drug in Canget BioTekpharma LLC (Canget) is a novel small molecule named FL118, discovered through compound library screening by using the cancer-associated survivin gene as a target and biomarker, followed by a series of in vitro and in vivo hit-to-lead analyses. FL118 has exceptional efficacy against advanced and treatment-resistant human tumors with a highly favorable toxicity profile [1-6]. For example, toxicity studies in beagle dogs with FL118 at the low, middle and high doses calculated from the mouse maximum tolerated dose (MTD) indicated that only at the high dose, a few of the 39 hematopoietic and biochemical parameters tested slightly changed (non-significant) without other FL118-related clinical observations including dog behavior, food consumption and body weights [6].

The chemical structure of FL118 is related to camptothecin (CPT) and CPT analogues, irinotecan, SN-38 (active metabolite of irinotecan) and topotecan (Fig 1). However, these CPTs use topoisomerase I (Top1) as the therapeutic target for their antitumor efficacy. Furthermore, these drugs are associated with high toxicity since Top1 is required for normal tissue renewal. Different from these CPTs, the antitumor efficacy of FL118 is not associated with Top1 expression [7]. Instead, FL118 shows high antitumor sensitivity and efficacy in human cancer with low/no Top1 expression [7]. This is consistent with our previous findings that FL118 inhibition of cancer cell growth occurs at the high pM to low nM range; whereas its effects on Top1 activity require µM levels [1]. FL118 selectively inhibits the expression of not only survivin, but also Mcl-1, XIAP and cIAP2 [1], MdmX/Mdm4 [5] and ERCC6 [6]. In contrast, SN-38 and topotecan exhibited 10-100 fold weaker in the inhibition of the expression of survivin, Mcl-1, XIAP and cIAP2 [1, 4]. Genetic silencing or overexpression of survivin, Mcl-1, XIAP and cIAP2 revealed their role in FL118 effectiveness [1, 3]. Furthermore, irinotecan, SN-38 and topotecan are the substrates of efflux pump proteins ABCG2/BCRP and Pgp/MDR1. In contrast, FL118 is not a substrate of them, and can bypass their treatment resistance [4, 8]. FL118 also overcomes a number of other common resistance factors such as cancer cells with mutated or null p53, and/or overexpression of MdmX/Mdm4 [5]. Additionally, our studies indicated that FL118 has a favorable pharmacokinetics (PK) profile because the FL118 drug accumulates in tumor [4] and is orally available [7]. FL118 effectively overcomes irinotecan and topotecan-resistant human tumors in animal models [4].

WE will now use human pancreatic ductal adenocarcinoma (PDAC) cancer as an example to show why and how FL118 is able to effectively eliminate PDAC patient-derived xenograft (PDX) tumors in animal models either alone or in combination with gemcitabine [6].

Through “Mannich Reaction”, a FL118 affinity purification column was made. Using the FL118 affinity column followed by mass spectrometry, we identified an ~70kD X-protein in the FL118 column, but not in the control column at the same stringent washing condition (Fig 2A). Our alternative protein microarray studies indicated that FL118 does not bind to other proteins in the same X-protein family, suggesting a reasonable specificity of the X-protein.

Importantly, the PDAC data from the Human Protein Atlas Database indicate that X-protein expression is enhanced in 83% of PDAC tumors (Fig 2B). Consistently, Western blot analyses of 3 normal pancreases (NP) and 7 PDAC PDX tumors indicated that while none of the 3 NP samples express X-protein, all the 7 PDAC PDX tumor samples express X-protein from high (PDX14244) to moderate/low (PDX12872) levels (Fig 2C). Intriguingly, although both PDX14244 and PDX12872 have mutant Kras (mKras), the differential expression of X-protein in these two PDX tumors is significantly associated with FL118 efficacy (Fig 2DE). Specifically, the PDX14244 tumor with high X-protein expression exhibits high sensitivity to FL118 treatment with only one cycle (Fig 2D), while the PDX12872 tumor with low X-protein expression exhibits much less sensitivity to FL118 treatment (Fig 2E). Of note, the re-grown tumor after treatment from PDX14244 is also much more sensitive to FL118 re-treatment than PDX12872 (not shown). Together, the data presented here strongly suggests that X-protein is a functional target for FL118, which can act as a biomarker and target for FL118 clinical trials for PDAC patient to increase FL118 response rate and avoid unnecessary treatment.


Fig 2 X-protein is the FL118 biochemical target and its expression is a good biomarker and target that is associated with PDAC tumor sensitivity to FL118 treatment: A. FL118 affinity purification identified a ~70kD X-protein (arrowed). FL118 was directly coupled to a beaded resin via a DADPA linker. Then, Cancer cell protein lysates were loaded on the FL118 column and control column in parallel. After stringent washing, proteins on the column were eluted with 8M urea buffers. After de-urea and concentrated to 20-30 μl using Nanosep 3k Omega (PALL), samples were display on a 5-20% gradient SDS PAGE gel and analyzed for protein identity using mass spectrometry. B. X-protein is overexpressed in 83% of PDAC tumors (Human Protein Atlas data). C. Expression of X-protein in 3 human normal pancreas (NP) and 7 PDAC PDX tumor samples is analyzed using Western blots. GAPDH is the total protein loading internal control. D. PDAC PDX14244 tumor curves after one cycle of vehicle and FL118 treatment. E. PDAC PDX12872 tumor curves after one cycle of vehicle and FL118 treatment. Method: PDAC PDX tumors were maintained on SCID mice. For experiments, SCID mice were implanted subcutaneously with 25-50 mg non-necrotic tumor tissues at the flank area of mice. When tumors reached 100-200 mm3 (defined day 0), FL118 was administered weekly for 4 times (arrowed) via intraperitoneal administration (ip) at 5 mg/kg (Of note, maximal tolerated dose = 10 mg/kg). Each curve represents mean ± S.D. (standard deviation) derived from five mice.

Our previous studies indicate that cancer cells without a functional p53 are more sensitive to FL118 treatment than cancer cells with wild type p53 (wtp53) [5]. Our most recent studies demonstrated that tumor cells with mutant Kras (mKras) are also more sensitive to FL118 treatment in comparison with tumor cells with wild type Kras (wtKras). A recent research article published in Nature demonstrated that the increase of the genetic amplification, aneuploidy and LOH-associated mKras dosage links to PDAC aggressiveness [9]. Intriguingly, loss of a functional p53 increases mKras dosage acquisition [9]. Loss of functional p53 can be resulted from point mutation, microdeletion or homocopolymer [10], which is collectively called mutant p53 (mp53). The mutation rate of p53 in PDAC is in the range of 50-70% [10-12], while the functional mutation rate of Kras in PDAC is in the range of 70-90% [11, 12]. More importantly, consistent with the finding that loss of functional p53 increases mKras dosage acquisition in PDAC [9], Kras mutation has a high association with p53 mutation in PDAC [11, 12]; mKras and mp53 can cooperate in the establishment of PDAC [11].

Consistent with the observations above, we found that when the PDAC PDX tumors have similar X-protein expression (Fig 2C), the p53 status and mKras expression level appear to play an important role in the determination of tumor sensitivity to FL118 treatment (Fig 3). Specifically, consistent with the finding that loss of a functional p53 increases mKras dosage acquisition [9], PDX10978 with wtp53 exhibits lower mKras expression than the expression level of mKras in the mp53-containing PDX19015 and PDX17624 (Fig 3A). Intriguingly, the PDAC PDX tumor sensitivity to FL118 treatment (Fig 3BCD) is roughly proportionate to mKras expression level (Fig 3A).

Fig 3 The p53 status in PDAC tumors may play a role in affecting mKras expression level, and mKras expression level is associated with PDAC PDX sensitivity to FL118 treatment: A. Expression of mKras in 3 human PDAC PDX tumors is analyzed using Western blots. GAPDH is the total protein loading internal control. B. PDAC PDX10978 tumor curves after one cycle of vehicle and FL118 treatment. C. PDAC PDX19015 tumor curves after one cycle of vehicle and FL118 treatment. D. PDAC PDX17624 tumor curves after one cycle of vehicle and FL118 treatment. E. Tumor curves of the same PDX10978 tumors used in B after FL118 combination with gemcitabine. Each curve in B to E represents mean  SD derived from five mice (5 mice per group). F, The same data shown in E were presented in the actual tumor volume to show the real size of the tumor during the experiments. Experiments: SCID mice were subcutaneously implanted with individual pancreatic cancer PDX tumors at the flank area of mice. Seven to 14 days after the implanted tumors grew to 100-200 mm3 (designated as day 0), FL118 was administered via intraperitoneal administration (ip) with a dose of about half maximum tolerated dose (1/2MTD, 5 mg/kg) (B, C, D) or with a dose of 0.75 mg/kg in combination with gemcitabine at 60 mg/kg (~1/2MTD) (E) weekly for 4 times (qw x 4) as shown (arrows).

Importantly, if a PDAC PDX tumor is not very sensitive to FL118 treatment such as the one used in Fig 3B (PDX10978), then use of low dose of FL118 in combination with a PDAC treatment standard drug (e.g. gemcitabine) could result in a complete elimination of tumors with just one cycle of treatment (Fig 3EF).

This is highly significant because in clinical treatment, cancer patients are typically treated with multiple treatment cycles until tumor progression and/or meeting toxicity impediment to continuing treatment. So in terms of FL118 use in the clinic, FL118 as a targeted anticancer drug would be used in multiple cycles until tumor complete elimination, which is an advantage in comparison with the usual one cycle of treatment animal model for cost effective in many cases.

Fig 4 Inhibition of X-protein by FL118 appears to go through ubiquitination proteasome degradation pathway: A. Inhibition of X-protein by FL118 is associated with inhibition of mKras protein and induction of apoptosis. PDAC MiaPaca2 cells with and without FL118 treatment for 24h are shown. Cells were then analyzed by Western blots with corresponding antibodies for the gene products as shown. B. Proteasome inhibitor MG132 could rescue FL118-mediated degradation of X-protein. PDAC MiaPaca2 cells were treated with and without FL118 in the presence and absence of MG132 for 24h as shown. Cells were then analyzed via Western blots with X-protein antibody. C. PDAC Panc1 cells were infected with lentiviral particles containing control shRNA, X-protein shRNA and mKras shRNA, respectively. Infected cells were lysed 48h post infection; the cell lysates were then used to determine the expression of X-protein and mKras expression using Western blots. GAPDH expression shown in A, B and C is the internal controls for total protein loading.

Our further studies indicated that while FL118 inhibits X-protein expression (Fig 4A), FL118 does not inhibit X-protein mRNA. This is consistent with the fact that FL118 directly binds to the X-protein (Fig 2A). Furthermore, inhibition of X-protein by FL118 can be rescued in the presence of proteasome inhibitor MG132 (Fig 4B), suggesting through an ubiquitination proteasome degradation pathway. Intriguingly, inhibition of X-protein by FL118 is associated with mKras expression inhibition, caspase-3 activation and PARP cleavage (Fig 4A). Activation of caspase activity and PARP cleavage are the hallmark of apoptosis.

Intriguingly, shRNA silencing of X-protein completely abrogates mKras expression, while shRNA silencing of mKras only weakly reduces X-protein expression (Fig 4C). This observation suggests that mKras is controlled by X-protein and is also one of the X-protein downstream targets.

In summary, FL118 appears to be a very promising candidate for effective treatment of the human PDAC cancer. FL118 is chemically and physiologically stable, orally available and accumulated in tumor after either oral, ip or intravenous (iv) administration. FL118 shows low toxicity to normal tissues. FL118 not only targets survivin but also targets and/or bypasses many other important oncogenic/antiapoptotic and treatment resistant protein factors (Fig 5). All of these unique characteristics of FL118 make FL118 a stand-out drug to eliminate cancer, especially PDAC cancer.

Why could FL118 target and bypass so many cancer-associated treatment resistant mechanisms? This is one of the major tasks that will be unraveled in the coming years.

Refer to the review article for survivin-targeting drug comparison and more information. https://jeccr.biomedcentral.com/articles/10.1186/s13046-019-1362-1

Additionally, we have demonstrated that FL118 is also a unique drug platform for generating novel FL118 analogues that could exhibit extreme high efficacy in certain cancer mutation situation for a more broad personalized precision medicine (see the “AI and FL118 platform Precision Medicine” section for more information).

References:

[1] Ling X, Cao S, Cheng Q, Keefe JT, Rustum YM, Li F: A Novel Small Molecule FL118 That Selectively Inhibits Survivin, Mcl-1, XIAP and cIAP2 in a p53-Independent Manner, Shows Superior Antitumor Activity. PLOS ONE 2012, 7:e45571.

[2] Ling X, Li F: An intravenous (i.v.) route-compatible formulation of FL118, a survivin, Mcl-1, XIAP, and cIAP2 selective inhibitor, improves FL118 antitumor efficacy and therapeutic index (TI). American Journal of Translational Research 2013, 5:139-54.

[3] Zhao J, Ling X, Cao S, Liu X, Wan S, Jiang T, Li F: Antitumor activity of FL118, a survivin, Mcl-1, XIAP, cIAP2 selective inhibitor, is highly dependent on its primary structure and steric configuration. Molecular Pharmaceutics 2014, 11:457–67.

[4] Ling X, Liu XJ, Zhong K, Smith N, Prey J, Li F: FL118, a novel camptothecin analogue, overcomes irinotecan and topotecan resistance in human tumor xenograft models. American Journal of Translational Research 2015, 7:1765-81.

[5] Ling X, Xu C, Fan C, Zhong K, Li F, Wang X: FL118 Induces p53-Dependent Senescence in Colorectal Cancer Cells by Promoting Degradation of MdmX. Cancer Research 2014, 74:7487-97.

[6] Ling X, Wu W, Fan C, Xu C, Liao J, Rich LJ, Huang RY, Repasky EA, Wang X, Li F: An ABCG2 non-substrate anticancer agent FL118 targets drug-resistant cancer stem-like cells and overcomes treatment resistance of human pancreatic cancer. J Exp Clin Cancer Res 2018, 37:240

[7] Li F, Ling X, Harris DL, Liao J, Wang Y, Westover D, Jiang G, Xu B, Boland PM, Jin C: Topoisomerase I (Top1): a major target of FL118 for its antitumor efficacy or mainly involved in its side effects of hematopoietic toxicity? Am J Cancer Res 2017, 7:370-82.

[8] Westover D, Ling X, Lam H, Welch J, Jin C, Gongora C, Del Rio M, Wani M, Li F: FL118, a novel camptothecin derivative, is insensitive to ABCG2 expression and shows improved efficacy in comparison with irinotecan in colon and lung cancer models with ABCG2-induced resistance. Molecular Cancer 2015, 14:92.

[9] Mueller S, Engleitner T, Maresch R, Zukowska M, Lange S, Kaltenbacher T, Konukiewitz B, Ollinger R, Zwiebel M, Strong A, Yen HY, Banerjee R, Louzada S, Fu B, Seidler B, Gotzfried J, Schuck K, Hassan Z, Arbeiter A, Schonhuber N, Klein S, Veltkamp C, Friedrich M, Rad L, Barenboim M, Ziegenhain C, Hess J, Dovey OM, Eser S, Parekh S, Constantino-Casas F, de la Rosa J, Sierra MI, Fraga M, Mayerle J, Kloppel G, Cadinanos J, Liu P, Vassiliou G, Weichert W, Steiger K, Enard W, Schmid RM, Yang F, Unger K, Schneider G, Varela I, Bradley A, Saur D, Rad R: Evolutionary routes and KRAS dosage define pancreatic cancer phenotypes. Nature 2018, 554:62-8.

[10] Redston MS, Caldas C, Seymour AB, Hruban RH, da Costa L, Yeo CJ, Kern SE: p53 mutations in pancreatic carcinoma and evidence of common involvement of homocopolymer tracts in DNA microdeletions. Cancer Res 1994, 54:3025-33.

[11] Pellegata NS, Sessa F, Renault B, Bonato M, Leone BE, Solcia E, Ranzani GN: K-ras and p53 gene mutations in pancreatic cancer: ductal and nonductal tumors progress through different genetic lesions. Cancer Res 1994, 54:1556-60.

[12] Yamaguchi Y, Watanabe H, Yrdiran S, Ohtsubo K, Motoo Y, Okai T, Sawabu N: Detection of mutations of p53 tumor suppressor gene in pancreatic juice and its application to diagnosis of patients with pancreatic cancer: comparison with K-ras mutation. Clin Cancer Res 1999, 5:1147-53.

Canget has a strong intellectual property (IP) protection for its technology.

Combining artificial intelligence (AI) and a series of FL118 platform-derived anticancer drugs for personalized cancer patient precision medicine

Background and our available data

As we described in our “Technology” section, cancer is a complex genetic and epigenetic disease with high genetic instability. Thus, most (if not all) types of cancer result from multiple gene mutations, deletion, amplification and/or aberrant gene expression (see the examples provided in the “Technology” section). Furthermore, the heterogeneity of cancer makes the effective treatment of cancer even more challenging. Tumors can have intra-tumor heterogeneity at different regions (i.e. different genetic and/or epigenetic alterations in different locations of an intra-tumor) [1] or at different metastatic sites of the same cancer patient (yet-to-be published observation from Canget and Roswell Park). Consistently, in the Christine Shaffer’s legacy story case (see Mr. Shaffer’s article under the “Patients” section in the Canget website), metastatic nodules in the lung and liver sites were very slow growing, yet tumor cells in the peritoneum metastatic site were very fast growing. One reason for this is due to additional genetic alterations. While such unique characteristics of cancer make effective cancer treatment very challenging, such a disease feature indicates a potentially effective approach to treat cancer by targeting and/or bypassing multiple genetic, epigenetic and aberrant gene expressing alterations.

We at Canget and Roswell Park have found that the chemical core structure of FL118 is a great novel drug-generating platform for producing a series of FL118 analogues with overlapping but distinct targeting scope profiles (see the “Major IP” sub-section for more information).

Figure 1: Expression of survivin and XIAP is increased in the SN38 8-month treatment-derived CRC cell sub-lines. Subconfluent HCT116 parental cells and its four sub-line derivatives (A2, SN50, C8, G7) were harvested and lysed for Western blots to analyze the expression of survivin, XIAP, Mcl-1 and cIAP2 using the corresponding antibodies. Actin was used as an internal control for equal protein loading. Of note, we did not find a significant change for Mcl-1 and cIAP2 expression (not shown).

The studies at Canget and Roswell Park indicate that certain types of FL118 analogues may possess unexpected, extremely high potency for killing cancer cells with certain genetic aberrations. For example, using the strategy of gradually increasing SN38 (active metabolite of irinotecan) concentrations to treat and select HCT116 colorectal cancer (CRC) cells for over an 8-month period, a series of treatment-resistant cancer cell sub-lines (A2, SN50, C8, G7) were generated. Limited analysis of the generated cell sub-lines indicated that they have different topoisomerase 1 (Top1) mutations with (A2, SN50) or without (C8, G7) ABCG2/BCRP overexpression [2]. However, it is reasonable to anticipate that through an 8-month period of SN38 drug stepwise pressure treatment, various genetic, epigenetic and aberrant gene expression changes may occur and these cancer cell sub-lines may have a high genetic diversity. This is the challenge that oncologists have to address when selecting chemotherapies to overcome treatment resistance. Consistent with this notion, we found both XIAP and survivin increased in these cancer cell sub-lines to make contributions to treatment resistance (Figure 1).

We then used these cancer cell sub-lines to determine the relative IC50 for six FL118 platform-derived analogues in parallel with FL118, SN38 and topotecan (Table 1). We found that while FL118 exhibited a broad-spectrum anticancer efficacy, certain FL118 analogues exhibited unexpected, extremely high potency to certain CRC cell sub-lines (Table 1, some examples are highlighted with a yellow background).

These observations trigger new perspectives and possibilities: We can develop a series of FL118 platform-derived analogues for personalized precision medicine to conquer cancers that possess different genetic, epigenetic and/or aberrant gene expression alterations. Importantly, this notion has been proven in the past 5 years through our studies of nearly a hundred of FL118 platform-derived anticancer drugs.

In summary, we believe that based on patient genetic, epigenetic and/or aberrant gene expression profiles, these personalized precision treatments for cancer patients using predefined FL118 platform-derived anticancer drugs would be synergistically enhanced and optimized through incorporation of the artificial intelligence (AI) and machine learning technology (see our forward perspectives and plan below).




Forward perspectives on AI-guided FL118 platform-derived anticancer drugs for personalized cancer patient precision medicine

1. Status of our current work: In the past three years or so, we have two active Biospecimens and Data Research (BDR) protocols for obtaining fresh CRC and pancreatic cancer tissues from the Roswell Park Clinic. These have been used to establish patient-derived xenografts (PDX) models for testing the tumor sensitivity to FL118 and FL118 platform-derived analogues in animal models. In parallel, the corresponding tumor tissues are also used for deep sequencing by using the next generation sequencing (NGS) technology to unravel the tumor molecular genetic profile. We believe that collection of antitumor efficacy data from human tumor animal model in parallel with collection of the molecular genetic profile from NGS analyses would be useful for establishing AI-guided databases for the sensitivity/efficacy linkage prediction of tumors with certain molecular profiles to FL118 or one of the FL118 platform-derived anticancer drugs.

2. Forward perspectives and a long-term work plan and methods: It is well known that making comparisons and event linkage predictions is highly subjective to human error and bias. In contrast, the AI and machine learning technology could significantly aid in making various optimal matches among multiple complex datasets. Specifically, we will create a database entry for each particular tumor’s drug sensitivity and efficacy so that an AI and machine-learning algorithm can be easily applied.

In parallel, we will establish a corresponding database that records each of the individual particular cancer patient tumors’ molecular genetic profiles into the AI and machine-learning algorithm. Through use of the AI and machine learning-guided databases-derived AI and machine-learning model, when a molecular profile information comes from a new cancer patient, it will be easy to match them to the correct drugs for personalized precision treatment. This would overcome a magnitude of variables and other factors that would result in gross errors of human interpretation of cancer. The concept of a tailorable drug platform such as the FL118 platform that is coupled with an AI-guided knowledge-based database created through continuous research over time could revolutionize cancer personalized medicine and precision treatment far beyond what is currently possible with just molecular profiling. Significantly, this will fill in a current urgent gap that exists where after a patient’s molecular profile is available, fewer drugs can be matched to the molecular profile. Actually, in most cases there is no drug that can match the patient’s molecular profile for a targeted precision treatment.

Importantly, with such an AI and machine-learning system we can refine the data in real time. Specifically, if we find any inaccurate linkage in our drug’s in vivo testing, we can go back into the AI model to adjust the corresponding parameter weight to improve the AI and machine-learning model. In other words, this is envisioned as a human and AI model exchange learning process. The bottom line is that through such reciprocal human-machine learning processes, the outcomes derived from the AI-guided deep learning model will be far beyond what a clinician is capable of. Furthermore, we have protein level data derived from proteomics analysis and transcriptome data derived from RNA-Seq analysis for some of individual PDX tumors. We can explore the possibility to add such data into the AI and machine-learning model for possibly increasing prediction accuracy.

Finally, as a long-term concept and goal of practice establishment, it is possible that Canget in collaboration with Roswell Park Hospital Clinic and/or other academic clinic could establish a virtual online hospital clinic. After online diagnosis and acquired patient’s molecular genetic information from the clinic electronic health records (EHR) as well as based on the prediction derived from the AI model, Canget will be able to directly express-mail the molecular genetic matching drug(s) derived from FL118 platform-derived anticancer drugs or FL118 itself to the treating physician for drug administration to the patients without the need to travel to the hospital. Of course, all of these processes will need to pass all required regulations including those mandates from the FDA. This long-term revolutionary conceptual practice of cancer treatment will be facilitated and accelerated by the coming era of digital health and digital science. Lastly and also importantly, such a virtual cancer patient treatment practice between the health care practice sites and pharmaceutical companies would also avoid the possible fake medicine issue provided by entities and/or persons elsewhere who have no authorization of right (e.g. a licensing agreement) in place.

References:

[1] Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P, Varela I, Phillimore B, Begum S, McDonald NQ, Butler A, Jones D, Raine K, Latimer C, Santos CR, Nohadani M, Eklund AC, Spencer-Dene B, Clark G, Pickering L, Stamp G, Gore M, Szallasi Z, Downward J, Futreal PA, Swanton C: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England journal of medicine 2012, 366:883-92.

[2] Gongora C, Vezzio-Vie N, Tuduri S, Denis V, Causse A, Auzanneau C, Collod-Beroud G, Coquelle A, Pasero P, Pourquier P, Martineau P, Del Rio M: New Topoisomerase I mutations are associated with resistance to camptothecin. Molecular cancer 2011, 10:64.

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