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. 2019 Sep 6;27(10):1706–1717. doi: 10.1016/j.ymthe.2019.09.002

The Landscape of Early Clinical Gene Therapies outside of Oncology

Laure Rittié 1,∗, Takis Athanasopoulos 2, Miguel Calero-Garcia 2, Marie L Davies 2, David J Dow 2, Steven J Howe 3, Alastair Morrison 4, Ida Ricciardelli 2, Aurore Saudemont 2, Laurent Jespers 2, Timothy M Clay 1
PMCID: PMC6822232  PMID: 31526597

Abstract

The field of cell and gene therapy (GT) is expanding rapidly and there is undoubtedly a wave of enthusiasm and anticipation for what these treatments could achieve next. Here we assessed the worldwide landscape of GT assets currently in early clinical development (clinical trial phase 1/2 or about to enter clinical trial). We included all gene therapies, i.e., strategies that modify an individual’s protein make-up by introducing exogenous nucleic acid or nucleic acid modifiers, regardless of delivery. Unmodified cell therapies, oncology therapies (reviewed elsewhere), and vaccine programs (distinct therapeutic strategy) were not included. Using a December 31, 2018 cutoff date, we identified 336 gene therapies being developed for 138 different indications covering 165 genetic targets. In all, we found that the early clinical GT landscape comprises a very disparate group of drug candidates in terms of indications, organizations, and delivery methods. We also highlight interesting trends, revealing the evolution of the field toward in vivo therapies and adeno-associated virus vector-based delivery systems. It will be interesting to witness what proportion of this current list effectively translates into new medicines.

Rittié et al. describe the worldwide landscape of gene therapy assets currently in early clinical development. They describe 336 gene therapies being developed for 138 indications covering 165 genetic targets. They also discuss the evolution of the field toward in vivo therapies and AAV-based delivery systems.

Main Text

The 2012 approval of alipogene tiparvovec (Glybera) as the first gene therapy (GT) for lipoprotein lipase deficiency,1 followed by that of Strimvelis in 2016 for the treatment of adenosine deaminase deficiency2 and voretigene neparvovec-rzyl (Luxturna) for biallelic retinal pigment epithelium-specific 65 kilodalton (RPE65) mutation-associated retinal dystrophy in 2017,3, 4 marked the beginning of the GT revolution. These approvals were paralleled by successful market authorizations in oncology with talimogene laherparepvec (Imlygic),5 tisagenlecleucel (Kymriah),6 and axicabtagene ciloleucel (Yescarta).7 Manufacturing processes, previously limited to small scale for clinical trials (CTs), were finally robust enough for commercial supply,8 with concerns for vector safety adequately addressed. Although manufacturing remains a bottleneck to commercialization,9 the field of GT has moved from concept to reality and boomed over the past few years. Indeed, the U.S. Food and Drug Administration (FDA) predicted 10–20 annual cell and GT drug approvals by 2025.10 As a result, there is renewed excitement and expectation for what GT treatments can next bring to patients.

Here we sought to evaluate the landscape of GTs in early clinical development. We included all GT candidates that met the American Society for Gene and Cell Therapy definition: “GT is the introduction, removal, or change in the content of a person’s genetic code with the goal of treating or curing a disease. The transferred genetic material changes how a single protein or group of proteins is produced by the cell. GT can be used to reduce levels of a disease-causing version of a protein, increase production of disease-fighting proteins, or to produce new/modified proteins.”11 Hence, probiotic-based therapies and non-genetically modified cell therapies were excluded. GT candidates were included regardless of delivery. We excluded oncology therapies (reviewed elsewhere12, 13) and vaccine programs (distinct therapeutic strategy). To our knowledge, this is the first survey of this type worldwide (de Wilde et al.14 covered the European landscape in 2016).

We mined searchable databases (including the U.S. National Library of Medicine, U.S. Clinical Trials registry, EU clinical Trials register, Cortellis, PubMed, and PharmaProjects) for GT candidates. We included all those in CT phase I and/or II (Ph.1/2) and GTs about to enter the clinic (e.g., Investigational New Drug [IND]-enabling studies started or IND application expected to be filed within a year). We excluded GT candidates that were tested in CT initiated years ago but had not been updated in the 5 years preceding our cutoff date of December 31, 2018. We used the World Health Organization International Classification of Diseases, 11th Revision15 to define disease families. All search results were curated and cross-verified with other sources, included companies’ press release materials, to verify conclusions and minimize misses. Our landscape analysis is presented below. All data were generated with the same exclusion and/or inclusion parameters for all figures.

Trends in the Global Early Clinical GT Pipeline

As of the end of 2018, we identified 336 GTs satisfying the search criteria above. Although spread across 11 medical fields (Figure 1A) and 51 disease families (Figure 1B; Table S1), these early clinical GTs are concentrated in a few medical specialties: 74% (250/336) of the identified GTs are from the top five medical specialties (hematology, endocrinology, neurosciences, cardiology, and ophthalmology). Similarly, 58% (195/336) of identified GTs concentrated on just eight disease families (inborn errors of metabolism, coagulation defects or related conditions, primary disorders of muscles, disorders of the retina, anemias or other erythrocyte disorders, movement disorders, diseases of arteries or arterioles, and primary immunodeficiencies). The other 42% (141/336) of GTs were spread among 43 additional disease families.

Figure 1.

Figure 1

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Trends in the Global Early Clinical Gene Therapy Pipeline

The 336 gene therapies were identified in 11 medical fields (A) and 51 disease families (per World Health Organization classification of diseases) (B). Bar colors in (B) refer to the respective medical field in (A). Details for (B) are given in Table S1.

The identified 336 early clinical GTs are directed toward 133 indications (not depicted): 45 indications are being explored by 3 or more GTs, 24 indications are the topic of 2 GTs, and 64 indications are being explored by only one. The most common indications are Duchenne muscular dystrophy (15 GTs), HIV infections (12 GTs), and hemophilia B (11 GTs). Neuropsychiatric disorders, addiction disorders, and gynecologic and/or urogenital disorders are notably absent from this list of indications. In summary, the observed distribution of GTs is pyramidal (top heavy with a very spread tail). It is likely that this distribution reflects both a historical perspective (blood disorders and eye and/or retina disorders were the first to show clinical success) and an advanced technology perspective (the field of GT is expanding to include more diseases). Time will tell whether high-medical-need diseases that are not currently actively being tested in CTs suffer from technology gaps, lack of deeper biological understanding and investment, or a combination of the above.

The Landscape of Genetic Targets

We observed a similar pyramidal distribution when evaluating the targets of current early clinical GTs (Figure 2): 92 GTs (27%) concentrate on 12 genetic targets (7% of investigated targets). In the middle of the distribution, 125 GTs (37%) are concentrating on 45 genetic targets (27% of the pool), while the bottom half of the distribution is much more spread out, with 65% of the overall genetic targets (107/164) being pursued by 107 GTs (32%). It is striking to note that the top two most studied targets have the highest rate of failure: VEGF (with 47% of programs halted, defined as discontinued, withdrawn, or terminated CTs) and the gene encoding the coagulation Factor IX, F9 (33% halted programs). Interestingly, halted programs include some of the oldest programs that meet our inclusion criteria (i.e., showing signs of activity within the 5 years preceding our cutoff date). There is no doubt that learning from these first-generation approaches increased our insight related to the choice of validated targets and technologies, leading to a better understanding of treatment regimens that can achieve therapeutic efficacy.

Figure 2.

Figure 2

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Trends in the Early Clinical Gene Therapy Pipeline Targets

The top 57 of 164 GT targets are being focused on by 2 GTs or more (depicted). An additional 12 early GTs are directed toward more than one target (GT targeting multiple target genes), and 107 additional targets are the focus of 107 additional GTs. Halted includes discontinued, terminated, and withdrawn CTs. CT, clinical trial; FTIH, first time in human; GT, gene therapy.

24% of GTs (81/336) currently in pre-clinical stage (pre-first time in human [pre-FTIH]) may seem surprisingly low. This is likely due to one of the limitations of our study, which includes only GTs that have applied for an IND or equivalent designation or disclosed an intent to apply for an IND (or equivalent) within a year. By opting in for this restriction, it is plausible that we missed some GTs (e.g., those with little or no communication before CT entry, such as those from large pharmaceutical companies). However, our intention was to focus on early CTs, and including GTs that were in the early discovery research phase would have skewed our observations.

Among the 81 identified pre-FTIH GTs, it is interesting to note the heavy representation of GTs targeting C9orf72, with four GTs about to enter CT (in addition to one already in the clinic). Dysregulated transcription of C9orf72 is linked to frontotemporal dementia, amyotrophic lateral sclerosis, or both (globally designated as C9FTD/ALS). Research on this topic is very active: a search on PubMed with ALS + C9orf72 returned 784 publications between the first publications in October 2011 and our cutoff date December 31st, 2018, and 174 publications for 2018 alone [search: “(C9orf72) AND (“2018/01/01”[Date - Publication]: “2018/12/31”[Date - Publication]) AND (amyotrophic lateral sclerosis) OR ALS”]. Although none of these publications described intervention approaches in humans, five GTs are already in early clinical phase, with one in the clinic. Different approaches are being considered, including gene replacement, gene editing, and silence and replace. This activity attests to the field’s willingness to move rapidly to capitalize on genetic insights for a disease with no current treatment and high unmet medical need. It will be interesting to see which approach proves most effective and how long it will take for these and/or future gene therapies to bring relief to affected patients and their families.

Key Players in the Early Clinical GT Pipeline

Most organizations involved with GT programs have only one GT each in early clinical development (107 organizations, i.e., 61%). Among the 38% of organizations developing 2 or more GTs, only 4.5% are big pharma (defined as large pharmaceutical companies of 50,000 employees or more) (Figure 3). This relatively small representation highlights the late entry of many big pharma companies into the GT field, compounded by a reluctance to publicize internal programs prior to clinical study start. Instead, there is a trend for biotech companies to partner with big pharma directly, which could also attest to the more cautious approach that big pharma is taking to GT. The recent spate of acquisitions of GT biotech companies suggests a shift in strategy by some big pharma companies.

Figure 3.

Figure 3

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The Landscape Analysis of the Key Players in the Early Clinical Gene Therapy Pipeline

67 of 174 organizations have two or more GTs in early clinical stage (as defined in the text), totaling 229 GTs. Among these organizations, 24% (16) are academic, governmental, and/or nonprofit groups (academia). Among the 107 one asset organizations, 29% (31) are academia. GT, gene therapy.

Remarkably, academic groups are developing 23% (77/336) of early clinical GTs and represent 27% (47/174) of the organizations surveyed (Figure 3). Academic groups tend to be hospital based or institutions with strong links to hospital centers. The NIH currently has seven GTs in early clinical development. When evaluating GTs in pre-FTIH versus post-FTIH stage, academic groups represent 5 and 45 organizations, respectively. This disparity likely highlights a difference in communication strategy rather than an innovation trend (unlike biotech companies, academic groups rarely publicly announce their intention to submit an IND application).

Industry sponsors approximately 77% (259/336) of CTs. Industrial CT prevalence possibly reflects the challenges faced by investigators moving experimental GTs into the clinic, a gap notoriously nicknamed the valley of death in the United States,16 a term that could be applied worldwide. Indeed, transitioning to clinical studies from pre-clinical validation requires significant funding to cover expenses, such as formal toxicology studies in animals, manufacturing of clinical-grade material and good manufacturing practice (GMP) reagents, preparation of regulatory documents, and costs at CT sites.9 Although government agencies are trying to meet the demand of CTs,17, 18 the reality is that most academic groups are slowed down by a lack of funding before attempting FTIH. Provided academic groups secured intellectual property (IP) rights to allow their discoveries to be commercialized,19 an option for them to secure clinical funding is to turn to venture capital funding by creating biotech companies before transitioning to FTIH. This has been the case at least in the United States and more recently in other countries, such as China.20 These much-needed investments efficiently jump-start clinical development.21, 22

Current Landscape of Delivery Methods for Gene Therapies

Our analysis shows that in vivo therapies currently dominate the early clinical GT space outside oncology (Figures 4A and 4B). Adeno-associated virus (AAV)-based transgene delivery is the most common in vivo delivery within early clinical GTs pre-FTIH (68% of in vivo therapies) and post-IND (58%). In the ex vivo space, which predominantly relies on ex vivo transduction of hematopoietic stem cells, lentiviral vectors (LVs) dominate the delivery approaches, for both pre-FTIH (69% of ex vivo gene therapies) and post-IND (56%). When separating the assets that are pre-FTIH (Figure 4A) from those in the clinic (with-IND, Figure 4B), we observed an increased proportion of AAV-based GTs in earlier programs (65% pre-FTIH versus 43% with IND) and a decrease in ex vivo approaches in earlier programs (16% pre-FTIH versus 27% with IND). It is important to note that the pre-FTIH with IND proportions represent two snapshots in time and are not indicative of future success in the clinic. Nevertheless, these proportions suggest that the current trend of AAV-based in vivo therapies dominating the GT space outside oncology might continue.

Figure 4.

Figure 4

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Analysis of Delivery Methods in the Early Clinical GT Pipeline

(A) 81 GTs are awaiting FTIH (pre-FTIH), with 84% (68) in vivo therapies, 65% (53) in vivo AAV therapies, and 11% (9) LV-mediated ex vivo therapies. (B) 255 GTs in phase 1/2 clinical trial (with IND) are made up of 73% (187) in vivo therapies, 43% (109) in vivo AAV therapies, and 15% (38) LV-mediated ex vivo therapies. FTIH, first time in human; GT, gene therapy; n.s., non-specified.

The preference for AAV-based delivery in the space was noticed at the pre-clinical stage a decade ago, with 38 CTs in the United States in 2008.23 The increased use of AAV in GT reflects the observation that ex vivo therapies can only tackle a subset of genetic diseases (ex vivo therapies have shown tremendous success toward hematological diseases and gene corrections targeting immune system reconstitution or those compatible with topical treatments, such as dermatological disorders). In contrast, in vivo therapies are aimed at targeting protein synthesis within cells and tissues. The in vivo LV therapies that have reached the clinic so far have been delivered by local surgical instillation and have not relied on intravenous delivery, with targeting based on the biology of the vector. Provided that AAV vectors can successfully reach target tissues, their use in the clinic dramatically increases the scope of diseases potentially treatable by GT. Together with an ongoing discovery of AAV serotypes that increase tissue or cell specificity and have less pre-immunogenicity,24 the AAV-based GT space indeed offers tremendous possibilities.

Some AAV-based GTs have already reached the market (alipogene tiparvovec or Glybera was an AAV-lipoprotein lipase, since withdrawn due to lack of commercial viability;25 voretigene neparvovec or Luxturna is an AAV-retinoid isomerohydrolase RPE65; and onasemnogene abeparvovec or Zolgensma is an AAV-based treatment for spinal muscular atrophy). This indicates that AAV can deliver sufficient and durable transgene expression to be considered therapeutic in certain tissues (with the caveat that AAV delivery is unlikely to give durable expression in dividing cells). To address the issue of durable expression with AAV delivery, one development option may reside in utilizing AAVs for stable modification, such as AAVs used for gene editing. Two such GT candidates are currently being tested in the clinic. They both use a combination of 3 AAVs (two AAVs to deliver a zinc-finger nuclease (ZFN) each and a third AAV to provide the payload for integration into the Albumin locus) to edit liver cells for the treatment of mucopolysaccharidosis types I and II.

Other potential approaches (e.g., AAV used in combination with transposons like sleeping beauty or PiggyBac or AAVs used to deliver donor DNA in combination with CRISPR delivered as ribonucleoprotein [RNP]) have yet to reach the clinic and are, therefore, not listed here. The 162 current CTs based on AAV delivery will help ascertain which serotype is best for what indication and whether the long-term transgene expression widely observed in animal models also occurs consistently in humans. However, AAV does have a small packaging capacity.23 While this may not represent a problem generally, it could become one as groups develop more complex mechanisms and/or control systems that will require larger payloads. This biological property alone warrants the need for other vector types, and, clearly, AAVs will not become the sole vectors used in GT in the future.

Many vectors have been tested over the years in CTs. A list of GT vectors (that includes those used in oncology and vaccines) is regularly updated by the Journal of Gene Medicine CT website.26 The obvious predominance of a subset of these vectors in current CTs may result from a combination of biological properties, historical settings (a group that finds a vector corresponding to their need will continue working with the same vector), and other factors (such as safety, toxicity, and ease of production). Remarkably, all pre-FTIH ex vivo programs (i.e., not yet in the clinic) disclose using LVs (none use non-LV retrovirus [RV], one uses an undisclosed viral delivery) versus 20% non-LV RV and γ-RV of ex vivo GT candidates in CT (Figure 4A versus Figure 4B). The main difference between LVs and γ-RVs is that LVs can transduce actively dividing and non-dividing cells and result in a safer integration profile (unlike γ-RVs that can only transduce mitotically active cell types).27, 28 It will be interesting to see if other serotypes, such as the measles and Nipah virus pseudotypes previously described in pre-clinical models,29, 30, 31 will be next to enter clinical trials.

Monogenic versus Non-monogenic Disorders

As discussed above, the upsurge of AAV-based CTs has dramatically increased the scope of diseases potentially treatable by GT. To better assess this aspect, we looked at monogenic versus non-monogenic disorders. Here, monogenic designates a disease caused by mutation(s) in one gene or one pair of alleles. For example, Leber congenital amaurosis (LCA) can be caused by a mutation in at least one of 14 genes, but a mutation in only one of these 14 genes is sufficient to cause LCA. LCA is thus a monogenic disease. Non-monogenic diseases can include complex genetic (multifactorial inheritance) or non-genetic causes (e.g., infectious diseases). Examples of non-monogenic diseases include HIV/AIDS infection, Parkinson’s disease, or congestive heart failure to cite the top three indications in this group. Monogenic disorders were historically the first to be targeted by GT, and it is not surprising that programs targeting monogenic diseases are now the most abundant in the clinic (64%, 215/336 GTs) (Figure 5A) and have led to two recent drug approvals (Luxturna and Zolgensma). Among those, 58% (125/215) pursue indications that are concentrated on four disease families (i.e., inborn errors of metabolism, primary disorders of muscles, coagulation defects or related conditions, and anemias or other erythrocyte disorders).

Figure 5.

Figure 5

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Comparison of Gene Therapies Targeting Monogenic versus Non-monogenic Disorders

(A) Distribution of GTs between monogenic and non-monogenic diseases. 58% of GTs (215/336) are aimed therapies for monogenic diseases. (B) Delivery methods used for early clinical programs targeting non-monogenic disorders. GT, gene therapy; n.s., non-specified.

The fact that one-third of the field is now targeting non-monogenic diseases is worth emphasizing. Non-monogenic diseases inherently require more complex therapeutic approaches than monogenic disease-targeting therapies, which are mainly gene addition (or augmentative) GTs. Since vectors can now be engineered to carry multiple genetic cargoes, addressing non-monogenic pathologies is a natural progression for the field. Improvements on delivery systems made in the last decade (e.g., better understanding of vector tropism, selection of more optimal vectors) means that these approaches can now be explored in the clinic. As a result, 76% of GTs that target non-monogenic diseases are in vivo-based delivery GTs. AAV delivery represents a significant portion of these (31 GTs and 19% of non-monogenic disease GTs), quickly followed by antisense oligonucleotides (ASOs) (23 GTs and 19% of non-monogenic disease GTs) (Figure 5B). Limited AAV payload capacity might explain why other vectors, or non-viral vector deliveries, are being tested in early CTs (17 additional GTs use in vivo non-AAV vector delivery and 44 GTs use in vivo non-virally injected nucleic acids) (Figure 5B). These trials will undoubtedly inform the field on a variety of topics, including vector toxicity, duration of effects, immune responses to vectors and payloads, and thus the feasibility of addressing non-monogenic diseases.

The Landscape of Genetic Suppression

Additional innovative approaches are currently being explored in the field, including that of genetic suppression. We identified 72 GTs related to genetic suppression, the vast majority of which aim to suppress the expression of a single gene (Figure 6A; Table S2). This is a subgroup of GTs that represent 21% of the early clinical landscape and thereby confirms the coming of age of genetic suppression applications in the clinic.32

Figure 6.

Figure 6

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The Landscape Analysis of Genetic Suppression in the Early Clinical Gene Therapy Pipeline

72 GTs in early clinical phase aim to repress protein expression via various mechanisms (CRISPR, suicide gene, mazF endonuclease, microRNA (miRNA)-small interfering RNA (siRNA)-shRNA, ASOs, SB, or ZFNs). (A) 35 GT candidates focus on 12 targets, 2 GTs each target multiple genes, and 35 additional candidates focus on a unique target. (B) 81% (58/72) of genetic suppression assets are in vivo therapies, delivered mostly by ASOs (51%) and AAVs (24%), and the remaining 19% (14/72) are delivered ex vivo via various means detailed in the figure. GT, gene therapy; n.s., non-specified. (C) Comparison of gene repression techniques delivered in vivo versus ex vivo and between industry-sponsored and non-industry-sponsored assets. ASO, antisense oligonucleotide; Env Ag, envelope antigen; GT, gene therapy; JCV, John Cunningham virus; PMO, phosphorodiamidate morpholino oligomer; n.s., non-specified; SB, sleeping beauty; ZFN, zinc-finger nuclease.

The DMD, HTT, BCL11A, CCR5, GATA3, and SOD1 genes are the most popular targets, with three or more GTs each. BCL11A is unique in the sense that this gene is targeted by the GT to alter the expression of another gene. This is the only exemplar of such an approach within the early clinical GTs we surveyed. BCL11A downregulates fetal hemoglobin (or γ-globin) production and exerts a critical role during the fetal-to-adult hemoglobin switch that occurs in humans shortly after birth.33 Sickle cell disease and β-thalassemia are both disorders of β-globin (the adult form of hemoglobin) and among the most common forms of genetic anemia in the world. The observation that BCL11A deletion results in γ-globin persistence in humans34 suggested that the therapeutic reduction of BCL11A levels could elevate γ-globin in patients with non-functional, mutated β-globin. This approach is currently being tested in the clinic using gene-editing tools to suppress BCL11A activity. At the time of this writing, it was too early to tell how beneficial this strategy would be to sickle cell disease patients. We look forward to seeing reports of the first clinical results.

As shown in Figure 6B, GTs aiming for genetic suppression are predominantly delivered in vivo using oligonucleotides (54%, 39/72), with the remaining deliveries being in vivo with AAVs (24%, 17/72) or ex vivo (19%, 14/72). The dominance of ASOs in this field reflects a combination of factors:35, 36 the technology is older than most gene-editing technologies (it has been in the clinic since 199837), and oligonucleotides’ action and delivery can be adjusted with various modifications.36, 38 Although delivery and consistent manufacturing remain a challenge, harnessing these RNA mechanisms and turning oligonucleotides into drugs is likely to become a bigger reality in drug development.

The large proportion of in vivo delivery using AAV reflects the trend observed across the early GT pipeline, as discussed in Figure 4. Ex vivo GTs that aim at genetic suppression mostly use non-viral delivery, mainly electroporation of isolated cells. Only three GTs utilize LVs and they all deliver small hairpin RNA (shRNA) (not depicted). This is in stark contrast to the gene addition technologies we discussed above.

Gene-editing-based GTs making our list include ZFNs, CRISPR/Cas9 (original acronym given for CRISPR/CRISPR-Associated-9), and RNAi, used both in vivo and ex vivo (Figure 6C). Transcription activator-like effector nucleases (TALENs) and meganucleases are noticeably absent from this list, albeit these technologies are being explored in oncology clinical studies. ZFNs were historically the first clinically applicable gene-editing tools and were developed in the early 2000s.39, 40 They entered the clinic in 2011 for HIV.41, 42 The CRISPR/Cas system is about a decade more recent (initially discovered in prokaryotes43 but quickly optimized for human cells with the addition of a nuclear localization signal and adaptation of single-guide RNA that can target any 20-bp DNA sequence44). Considering this 10-year age difference between the two systems, it is remarkable to find six GTs for CRISPR/Cas9 along with ten ZFN GTs. This shows that the youngest of the genome-editing technologies is bridging the gap to the clinic very swiftly.

The pros and cons of the various gene-editing platforms, potential therapeutic applications, and potential safety concerns have been reviewed elsewhere45, 46, 47 and are beyond the scope of this review. When considering the relative merits of RNAi and genome editing for a given target, it is a common mistake to solely focus on the level of reduction in gene expression. This topic has been reviewed elsewhere,48, 49 and the reader is urged to take the issues raised in these reviews (including residual levels of expression, selectivity, precision delivery, and overall control of the system) into consideration.

Most genetic suppression-based clinical GTs are being developed by industrial organizations (Figure 6C). This strong bias toward industry likely reflects the relatively complex IP landscape of the field of genetic suppression in general and gene editing in particular. This is especially true for CRISPR/Cas systems, where the IP landscape is currently very complex. The eukaryotic application of the initial discovery claimed by both the Charpentier, University of California-Berkeley, and Vienna groups50 and the Broad Institute, MIT, and Harvard groups51 is still being disputed.52 In the meantime, more than 3,800 patent families and over 110 licensing agreements for CRISPR/Cas were filed/signed from 2014 to January 2019.53 Time will tell if the complexity of the current IP situation will hamper the development of future CRISPR/Cas-based therapeutics.

The Landscape of Ex Vivo Therapies

We also took a closer look at ex vivo GTs, as this technology has proven clinical efficacy (Strimvelis was launched in 2016 and Zynteglo received conditional marketing authorization from the European Medicines Agency in 2019). We identified 81 ex vivo GTs. As shown in Figure 7A, CTs are ongoing for 79% (64/81) of these while the remaining 21% are in the late stage of pre-clinical development. Most anemias or other erythrocyte disorders are being tested with ex vivo approaches (compare Figures 1 and 7A), and HIV disease, primary immunodeficiencies, and genetically determined epidermolysis bullosa are disease families for which most GTs utilize ex vivo therapies. The top three disease families comprise GTs that directly target blood cells. This reflects the fact that ex vivo delivery remains the technology of choice where the main GT carriers are cells of the hematopoietic lineage (as is the case in the oncology space). This observation is not restrictive, however, as we identified a quite broad medical application outside these three leading disease families.

Figure 7.

Figure 7

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The Landscape Analysis of Ex Vivo Gene Therapies

(A) 81 GTs aim to be delivered ex vivo for indications encompassing 22 disease families. 83% (68) of these GTs have authorization to conduct clinical trials (IND or equivalent). (B) Gene targets for ex vivo GTs in early clinical phase. 42 individual targets are being tested by 75 ex vivo GTs and 6 ex vivo GTs target multiple genes each. (C) Technologies used by ex vivo-modified early clinical gene therapy assets. 75% (61) of ex vivo-delivered GTs use retroviral delivery (LV or other RV) to modify target cells. GT, gene therapy; n.s., not specified.

The majority (93%, 75/81) of ex vivo GTs target a single gene (Figure 7B): 42 genetic targets are being tested by 81 ex vivo GTs and only 6 GTs target multiple genes. The delivery approaches employed by ex vivo GTs are rather uniform: 61% (61/81) employ RVs and 8 assets (10%) are non-specified (could be RV or something else) (Figure 7C). Among RVs, LVs appear as the dominant delivery system for GTs that require integrating technology (utilized by more than 50% of ex vivo therapies). In all, the predominance of RVs/LVs delivery reflects the fact that these approaches are viewed as the right tool for a subset of target cell types (e.g., T cells and hematopoietic stem cells).

Aside from RVs/LVs, the ex vivo GT field also includes a few innovative delivery technologies that encompass many other viral and non-viral approaches. These few GTs are being developed by many one-clinical GT organizations, all from industry (Figure 7C). As opposed to demonstrating a lack of innovation from academia, we believe this reveals a frequent strategy of spinning-out biotech companies from academic groups before CTs begin, as discussed above.

Geographical Location of Early Clinical Trials in GT

The early clinical GTs we identified are being conducted in 26 countries (Figure 8). Most GTs are being tested in the United States (54%), with the top six countries (USA, UK, France, China, Canada, and Germany) hosting 85% of GT early phase CTs; 10% of the surveyed GT CTs are being conducted, at least in part, in Asia (China, Japan, Korea, and Taiwan). In Europe, the UK and France are positioned as leaders for non-oncology GTs, although some of the early pioneers such as Italy, having developed GTs now in phase 3 or launched, may seem under-represented in our study. Overall, the differences existing between the United States versus Europe and the USA versus Asia are striking.

Figure 8.

Figure 8

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Analysis of the Geographical Locations of the Early Clinical Gene Therapy Pipeline

The early clinical GTs surveyed here are being developed by organizations originating from 26 countries around the world. The top 6 countries (USA, UK, France, China, Canada, and Germany, respectively) host 83% of the CTs. Clinical trials’ main sponsors were considered. In the cases where CTs were split among several countries, each country was represented with a count of 1. GT, gene therapy.

Importantly, our overall results might be biased by the following factors. First, we only accessed English-written material or material that was translated into English (in whole or summary). Thus, we might have missed some of the CTs originating from parts of the world where scientific communications are not systematically translated (e.g., China and Japan). Second, the United States has a federal mandatory requirement to register CTs on a public database. This is not the case for all countries, and CTs that are not listed on a major database will not appear on our list. Practically, the reader should keep in mind that uneven access to information inherent to worldwide work may translate into a more complete record for the United States than other countries and, conversely, an underestimation of non-USA GTs in our count. Some authors have drawn attention to the underestimated contribution of Asian countries to the GT field in the past.54, 55

Apart from accessibility of information, a few additional factors might influence a country’s activity in the GT space. Advances in the GT field require a tremendous amount of scientific work with support from government agencies, academic institutions and hospitals, and commercial sponsors. Some regulatory agencies are more familiar with GT applications, and this may make the regulatory path clearer and more expeditious than others.56, 57, 58, 59, 60, 61 For example, in changes proposed on August 17, 2018, in the Federal Register, the American NIH and FDA seek to reduce the existing duplicative oversight burden from the NIH and the Recombinant DNA Advisory Committee (RAC). Specifically, these proposals will eliminate RAC review and reporting requirements to the NIH for human GT protocols. RAC will still be involved in emerging technologies such as gene editing for the time being.62 This represents an important step toward integrating GT regulation within the existing oversight system, and it signals that GTs are now officially out of their tryout period from an American regulatory standpoint.

It is currently impossible to predict if there will be a geographic shift of CTs as the field advances. Similarly, it is hard to predict how much companies currently involved in developing pioneering treatments will expand access to the resulting medicines to other densely populated regions (e.g., India and Africa), such as by creating localized hubs and/or GT centers of excellence in these regions.

Conclusions

The GT space is rapidly expanding. Tang et al.12 recently reported 401 immuno-oncology GTs in Ph.1/2 (data cutoff of September 2018). Here we report an additional 336 GTs in early clinical development outside of vaccines and oncology (data cutoff of December 2018). This attests to the excitement that currently surrounds the GT space and the tremendous opportunity this therapeutic approach represents.

Our study highlights several important trends in addition to the rapidly expanding space underscored above. Notably, GT is no longer an experimental science that focuses on fundamental questions using a few disease models. Monogenic disorders were the first to be targeted by GT in the clinic, and they still represent two-thirds of GT candidates in early clinical development described here. In addition, the field has clearly begun to expand across a wider range of indications. The power of genetics coupled with functional genomics continues to unravel complex disease biology and, with it, our understanding of genetic associations in the mechanism of action of diseases. We believe that the field will continue to expand in this new direction and tackle more non-monogenic, complex diseases in the future. It is likely that this trend will require developing specific delivery systems able to deliver several genes at a time or multiple genes to several tissues or cell types. We look forward to witnessing future progress in that direction.

Undoubtedly, the field has evolved toward in vivo therapies and AAV-based delivery systems. AAVs are currently the approach of choice to target specific organs or cell types. We believe this trend toward targeted delivery will continue, not only with AAVs (e.g., through the development of more targeted AAV serotypes) but also with other virus types (e.g., measles and Nipah pseudo-typed lentiviruses discussed above) and non-viral systems. Because gene editing offers the advantage (and risk) of being permanent, improvement of delivery precision is a sine qua non condition to the successful development of gene-editing approaches, in our opinion. Together with additional improvements, such as the control of expression using switch technology or other means, targeting and precision are bound to improve in the next few years.

We also believe the field must circumvent the current hurdles associated with re-treatment. Many AAV treatments trigger some level of immunity to the vector, which prevents potential re-treatment once the GT’s primary effects start to wane. Re-treatment can theoretically be achieved by utilizing less immunogenic viral pseudotypes,63 non-viral deliveries,64 or adjuvant treatments aimed at mitigating the immune response induced by the GT in the first place.65 All these options currently show promising outcomes in pre-clinical models, provided their manufacturing can be controlled in large scale.66 It will be interesting to see if these different approaches (or their combination) are as successful in the clinic as they were in pre-clinical models.

Finally, although equitable access to GT in high-income countries remains challenging, it is even more difficult for patients in low- and middle-income countries, and active global health outreach programs are desperately needed.67, 68 This is an exciting time, but much remains to be done to address the remaining technological challenges and expand GT development to many more diseases and more countries. It will be interesting to witness how many on this current list of early clinical GTs translate into new medicines for our patients.

Author Contributions

Conceptualization and Methodology, L.R., L.J., and T.M.C.; Data Collection and Analysis, L.R., T.A., M.C.-G., M.L.D., D.J.D., S.J.H., A.M., I.R., A.S., and T.M.C.; Writing – Original Draft, L.R. and T.M.C.; Writing – Review and Editing, all authors.

Conflicts of Interest

The authors declare no competing interests.

Acknowledgments

The authors would like to thank IQVIA for their assistance with data collection and Dr. Thorsten Friedel for his insightful comments during the revisions of this manuscript. The views and opinions expressed herein are those of the authors and do not necessarily reflect the official policy or position of GlaxoSmithKline (GSK).

Footnotes

Supplemental Information can be found online at https://doi.org/10.1016/j.ymthe.2019.09.002.

Supplemental Information

Document S1. Tables S1 and S2
mmc1.pdf (293.3KB, pdf)
Document S2. Article plus Supplemental Information
mmc2.pdf (3.4MB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Tables S1 and S2
mmc1.pdf (293.3KB, pdf)
Document S2. Article plus Supplemental Information
mmc2.pdf (3.4MB, pdf)

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